CN106547858A - A kind of air conditioning unit big data analysis method and air conditioning unit - Google Patents

A kind of air conditioning unit big data analysis method and air conditioning unit Download PDF

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Publication number
CN106547858A
CN106547858A CN201610916991.7A CN201610916991A CN106547858A CN 106547858 A CN106547858 A CN 106547858A CN 201610916991 A CN201610916991 A CN 201610916991A CN 106547858 A CN106547858 A CN 106547858A
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CN
China
Prior art keywords
air conditioning
conditioning unit
data
monitoring module
service data
Prior art date
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Pending
Application number
CN201610916991.7A
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Chinese (zh)
Inventor
彭嘉欣
钟金扬
董玉红
关富文
黎开晖
曾俊杰
谢华文
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Gree Electric Appliances Inc of Zhuhai
Original Assignee
Gree Electric Appliances Inc of Zhuhai
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Gree Electric Appliances Inc of Zhuhai filed Critical Gree Electric Appliances Inc of Zhuhai
Priority to CN201610916991.7A priority Critical patent/CN106547858A/en
Publication of CN106547858A publication Critical patent/CN106547858A/en
Pending legal-status Critical Current

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Classifications

    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/30Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/62Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00Control inputs relating to air properties
    • F24F2110/10Temperature
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2120/00Control inputs relating to users or occupants
    • F24F2120/10Occupancy
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/20Administration of product repair or maintenance
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/30Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F24F11/32Responding to malfunctions or emergencies
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/50Control or safety arrangements characterised by user interfaces or communication
    • F24F11/52Indication arrangements, e.g. displays
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2216/00Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
    • G06F2216/05Energy-efficient information retrieval

Abstract

The present invention relates to a kind of air conditioning unit big data analysis method and air conditioning unit, this is air conditioning unit to be connected with for monitoring the monitoring module of its service data, the monitoring module transmits the service data Jing communication module to server, the server is stored in the service data in data base, processing system transfers the service data in the data base, and server and the communication module according to service data Jing sends to the monitoring module and instructs, the monitoring module sends information according to the instruction for receiving and/or controls the air conditioning unit operation.Air-conditioning fault rate can effectively be reduced using air conditioning unit big data analysis method of the invention;After breaking down, by analyzing reason, abort situation is locked, when display shows unit picture, failed part can show obvious color, help user or after-sales service personnel maintenance;Make air-conditioning more comfortable, it is more humane, and allow unit to become Automatic Control air-conditioning.

Description

A kind of air conditioning unit big data analysis method and air conditioning unit
Technical field
The present invention relates to field of air conditioning, more specifically it relates to air conditioning unit big data analysis method and adopt the method It is air conditioning unit.
Background technology
When the air conditioning unit operational factor in running of air conditioning unit especially large commercial deviates critical field still State can be remained on until producing failure, the infringement to unit is larger and fault rate is higher, further, since after-sales service personnel The reason such as lack experience, investigation failure cause is difficult, affects maintenance efficiency.
The content of the invention
In view of this, it is an object of the invention to provide a kind of air conditioning unit big data analysis method and air conditioning unit, which can To solve following technical problem:After-sales service personnel lack experience, and investigation failure cause is difficult;Business air conditioner unit fault rate It is high;Display interfaces show that solidification is dumb.
Air conditioning unit big data analysis method of the invention, its technical scheme is:
A kind of air conditioning unit big data analysis method, it is described air conditioning unit to be connected with for monitoring the monitoring of its service data Module, the monitoring module transmit the service data Jing communication module to server, and the server is by the operation number According to being stored in data base, processing system transfers the service data in the data base, and according to service data Jing Server and the communication module send to the monitoring module and instruct, and the monitoring module sends prompting according to the instruction for receiving Information and/or the control air conditioning unit operation.
Air conditioning unit big data analysis method of the invention, processing system can in real time to air conditioning unit operation number According to being monitored and sending instruction according to air conditioning unit service data item monitoring module, corresponding information alert and control are carried out The air conditioning unit operation of system, so as to be reminded in real time and parameter adjustment when air conditioning unit service data occurs abnormal, Reduce air conditioning unit fault rate.
Preferably, the standard service data for being stored with air conditioning unit in the data base, the processing system are transferred described Real-time running data and standard service data in data base, the real-time running data is entered with the standard service data Row compares, when the value of the real-time running data is closed on or during beyond the marginal value of standard service data, the processing system Send to the monitoring module via server and communication module and instruct, the monitoring module is carried out according to the instruction for receiving It is corresponding to show and/or parameters revision.
Preferably, the standard service data is obtained according to the historical data being stored in the data base, or, it is described Standard service data is pre-stored in the data base.
Preferably, the standard operation according to the historical data being stored in the data base to being pre-stored in the data base Data are modified.
The analysis method that the present invention is provided is come right based on same type or identical air conditioning unit long history service data The method that air conditioning unit real-time running data is analyzed, the Data Analysis Model obtained by which is from the horse's mouth, so as to analyze Resulting result accuracy rate is high, in addition, can be repaiied to the standard service data being pre-stored in data base according to historical data Just, that is, there is learning process, can further optimisation criteria service data, so as to further improve precision of analysis.
Preferably, corresponding display includes the display of trouble unit, air conditioning unit display the reason for break down And/or the type of alarm command.
For example, corresponding trouble unit can be shown, is investigated in order to staff, further can be by failure portion Part is shown with special color and intuitively identify trouble unit in order to staff.Or, for example, can be by failure Instruction output indicates the air conditioning unit problem for running into of staff on monitoring module (such as display).
Preferably, the learning data includes air conditioning unit leaving water temperature, local temperature, air conditioning unit average load, electricity Stream situation, and/or voltage condition.
Preferably, processing system is by the air conditioning unit leaving water temperature in air conditioning unit real-time running data, local high-temperature, Air conditioning unit leaving water temperature in air conditioning unit average load and learning data, local temperature, air conditioning unit average load are compared Compared with when local temperature is raised, and air conditioning unit average load is raised, accordingly increasing air conditioning unit leaving water temperature and arrange to realize section Can effect.
Preferably, the processing system is by the standard service data stored in data base and the air conditioning unit real time execution Data are compared analysis, judge air conditioning unit running status whether normal and energy-conservation, and according to judged result, work as air conditioner When exception or low efficiency occurs in the running status of group, adjust instruction is provided, monitoring module ejects corresponding according to adjust instruction The content of adjust instruction and/or carry out parameters revision.
Preferably, the processing system is by the air conditioning unit leaving water temperature in air conditioning unit real-time running data, local ring Air conditioning unit leaving water temperature, local environment temperature in border temperature, air conditioning unit average load and standard service data, air conditioner Group average load compares, and when local environment temperature is raised, and air conditioning unit average load is raised, sends to the monitoring module Adjust instruction, the monitoring module eject whether improve the prompting of air conditioning unit leaving water temperature or by air-conditioning according to adjust instruction Unit leaving water temperature is improved.
Preferably, the air conditioning unit real-time running data is included one before and after the sampling time point for setting or fault time point The air conditioning unit real-time running data of whole in the section time.
Preferably, described a period of time is 30 minutes.
When needing to sampling time point, or find that the data near the air conditioning unit time point for exception/fault occur are entered During row analysis, processing system can be analyzed ratio using the air conditioning unit real-time running data obtained in a period of time Compared with to obtain expectation and more accurate result.
Preferably, the monitoring module is display apparatus module
Display apparatus module intuitively exports analysis result or unsuitable operational factor is directly modified, in order in sky When adjusting unit operation to occur abnormal, staff efficiently has found and solve problem in time.Display apparatus module in this includes showing Show device, but which is not merely display, which is a multifunctional intelligent terminal system, the intelligent terminal system can be realized The several functions such as data sampling, data transfer, data display, data input, data modification.
Preferably, the communication module is GPRS module.
It is of the invention air conditioning unit, using big data analysis method as above.
Had the advantages that using air conditioning unit big data analysis method of the invention:It is air conditioning unit to carry Front early warning, reduces air-conditioning fault rate;After breaking down, by analyzing reason, abort situation is locked, unit is shown in display During picture, failed part can show obvious color, help user or after-sales service personnel maintenance;Make air-conditioning more comfortable, more human nature Change, and allow unit to become Automatic Control air-conditioning.
Description of the drawings
By description referring to the drawings to the embodiment of the present invention, above-mentioned and other purposes of the present invention, feature and Advantage will be apparent from, in the accompanying drawings:
Fig. 1 is the controller analysis of air conditioning unit big data analysis method of the invention and response architecture figure;
Fig. 2 is the load data of the air conditioning unit longtime running of the air conditioning unit big data analysis method using the present invention Figure;
Fig. 3 is the air conditioning unit concrete data value in Fig. 2.
Specific embodiment
Below based on embodiment, present invention is described, but the present invention is not restricted to these embodiments.
The framework of the air conditioning unit big data analysis method that the present invention is provided is, air conditioning unit to be connected to monitor its operation The monitoring module of data, monitoring module transmit service data Jing communication module to server, and service data is stored by server In data base, the service data in processing system called data storehouse, and according to service data Jing server and communication module to Monitoring module sends instruction, and monitoring module sends information according to the instruction for receiving and/or controls air conditioning unit operation.
Wherein, monitoring module obtains each air conditioning unit real-time running data for being connected with air conditioning unit mainboard, Which can be controller, preferably display apparatus module.Communication module connects for communication is set up between monitoring module and server Relation is connect, so as to convenient data transfer each other, it is preferable that communication module is GPRS module.Data base can be built in clothes On business device.Processing system is application program, and which can be implemented in intra-company's system, hereinafter referred to intelligent Service center.
Fig. 1 shows the controller point of the air conditioning unit big data analysis method provided according to the specific embodiment of the invention Analysis and response architecture figure.
The data transfer flow direction of air conditioning unit big data analysis method of the invention is as follows:
Air conditioning unit real-time running data is transferred to data base:
The air conditioning unit service data of display apparatus module monitor in real time, and air conditioning unit real-time running data is issued into GPRS moulds Block;GPRS module is got in touch with server, data is issued data base by server by being wirelessly transferred;Data base's handle All of data are all preserved;Data are processed by intelligent Service center.
Send instructions to scene after data analysiss:
After intelligent Service center analysis data, to sending instructions under server, instruction is transferred to display by GPRS module Module;Whether there is teledata in display apparatus module detection data bus, if it has, processing to data, change display The display content of module.
Air conditioning unit big data analysis method of the invention carries out data processing:The data processing includes troubleshooting And energy-efficient treatment.The processing procedure that troubleshooting is carried out when air conditioning unit running status occurs abnormal, energy-efficient treatment is When the processing procedure that carries out when efficiency is low occurs in air conditioning unit running status.
Wherein, troubleshooting is divided into two kinds of processing modes, and a kind of is the processing mode before failure occurs, and one kind is that failure goes out Processing mode after now.
Before failure occurs:The air conditioning unit real-time running data of intelligent Service center real-time monitoring, when the temperature of unit operation After the data such as degree, pressure, power consumption reach predetermined critical point, warning can be sent, staff can be to air conditioning unit state again Check.
Wherein it is possible to use fault early-warning detection method:
After staff is air conditioning unit at intelligent Service center connection scene, the real time execution number of monitoring air conditioner group According to, and the standard service data stored in called data storehouse, real-time running data is compared with normal data, is transported when in real time The value of row data close on or beyond the marginal value of standard service data when, intelligent Service center is via server and GPRS module Send to display apparatus module and instruct, display apparatus module is shown and/or parameters revision accordingly according to the instruction for receiving.Its In, standard service data can be pre-stored in data base, and its source is the experiment under each operating mode of the laboratory technician when unit is tested The record data of maximum, the minimum and standard value occurred in data, this sets of data using according to the exclusive unit bar code of unit as Differentiation is entered in the data base of each unit.The historical data that standard service data can be stored in data base according to is obtained , in addition, can also be repaiied to the standard service data being pre-stored in data base according to the historical data being stored in data base Just, that is, there is learning process, can further optimisation criteria service data, so as to further improve precision of analysis. If centrally through database data, intelligent Service detects that each important parameter exceedes the maximum of " normal data ", minima, will be prompted to Which parameter overruns, and staff can check set state by remote monitoring inside, when substantially reducing access Between, if cannot remotely solve, made using the air conditioning unit unit or air conditioning unit producer scene of will sending someone To look back after sale, further checked to air conditioning unit.
After failure occurs:If scene has occurred in that failure, failure can be learnt by data analysiss in intelligent Service center Which occur on part or part, the unit schematic diagram on display apparatus module can be shown as obvious trouble unit automatically Where color, inform user malfunction appearance, and by after-sale service, personnel follow up;Simultaneously intelligent Service center also can remotely control, See the failure that the scene of whether being solved by the method for remotely located parameter is caused as parameter setting is improper.
Wherein it is possible to use failure analysis methods:
When air conditioning unit faulty, display apparatus module can be fault flag (time point for breaking down) by logical The mode of news issues GPRS module, so as to trigger GPRS module 30 minutes before and after fault flag (30 minutes herein be one Individual setting value, can be configured according to real needs, be not limited to be 30 minutes) data all upload in data base, Can be intelligent Service center according to the data of 30 minutes before and after fault flag in the automatic called data storehouse of fault flag, from It can be seen that the situation of change of each second of data, from control logic, which position of relative analyses goes wrong in data base. In one specific embodiment, if the failure of unit prompting " current imbalance ", failure cause is:Compressor host A, B, C Three-phase current IA, IB, IC, compared with three-phase average current I1, when (IA-I1)/I1, (IB-I1)/I1, (IC-I1)/I1 its Middle have one mutually or multiphase >=20% continues 10S, that is, report " current imbalance " failure, herein 20% be only an example, tool Body numerical value can be according to three-phase current deviation setting.After so occurring in that the failure, data can be recalled from data base and seen Which phase deviation is larger on earth for A, B, C phase current, and maintainer can be directly locked according to being which phase current difference causes imbalance Concrete circuit.Or to judge whether that three-phase current error set point is set to unreasonable, it is also possible to by whether checking the parameter Check according to corporate policy file configuration.Remaining malfunction elimination method is similar to, and is all according to 30 minutes before and after detection failure Data meet the condition of reporting an error locking which parameter, point out malfunctioned parameter, and the time of error, side over the display Help Field Force's direct analysis.
The specific embodiment of energy-efficient treatment is described below.
Fig. 2 shows the load of the air conditioning unit longtime running of the air conditioning unit big data analysis method using the present invention Datagram;Fig. 3 shows the air conditioning unit concrete data value in Fig. 2.
According to Fig. 2 and Fig. 3, further illustrate how air conditioning unit big data analysis method of the invention is realized Energy-efficient treatment.
As a example by the analysis of Fig. 2 and Fig. 3, can be by air conditioning unit leaving water temperature, air conditioning unit load, local environment most High-temperature etc. analyses whether to need to point out user, and load is too high, can suitably increase air conditioning unit leaving water temperature, thus both can be with Moderate temperature is reached, the effect of energy-conservation can be reached again.
For example, as shown in Fig. 2 user is 7 degrees Celsius " chilled water water outlet temperature setting ", collect back according to GPRS module The area come although it is understood that the maximum temperature of locality, and according to the change of temperature, analysis is obtained when local environment temperature is higher, " chilled water water outlet temperature setting ", to after lower temperature, air conditioning unit load is big, and air conditioning unit load conference causes power consumption many, no Beneficial to energy-conservation.This when remote analysis to data display apparatus module, display apparatus module bullet can be passed to by GPRS module Go out warm tip:Can be conducive to energy-conservation " chilled water water outlet temperature setting " slightly turned up, and also can keeping temperature relax It is suitable.
Air conditioning unit user's effect using air conditioning unit big data analysis method operation of the invention is as follows:
For user's power saving, energy-saving effect is reached;
The failure problems for having solved to occur before user's unit not up to failure can be shifted to an earlier date, if there is part damage The failure such as bad, can eject the prompting of close friend over the display, point out user concrete abort situation, and contact in time is changed after sale Deng.
Air conditioning unit manufacturer's effect using air conditioning unit big data analysis method operation of the invention is as follows:
Lower fault rate;It is easy to misarrangement after sale.
The preferred embodiments of the present invention are the foregoing is only, the present invention is not limited to, for those skilled in the art For, the present invention can have various changes and change.All any modifications made within spirit and principles of the present invention, equivalent Replace, improve etc., should be included within the scope of the present invention.

Claims (13)

1. a kind of air conditioning unit big data analysis method, it is characterised in that:Air conditioning unit being connected with is run for monitoring which The monitoring module of data, the monitoring module transmit the service data Jing communication module to server, and the server will The service data is stored in data base, and processing system transfers the service data in the data base, and according to the operation Server described in data Jing and the communication module send to the monitoring module and instruct, and the monitoring module is according to the finger for receiving Order sends information and/or controls the air conditioning unit operation.
2. method according to claim 1, it is characterised in that the standard operation for being stored with air conditioning unit in the data base Data, the processing system transfer the real-time running data in the data base and standard service data, by the real-time fortune Row data are compared with the standard service data, when the value of the real-time running data is closed on or runs number beyond standard According to marginal value when, the processing system sends to the monitoring module via server and communication module and instructs, the monitoring Module is shown and/or parameters revision accordingly according to the instruction for receiving.
3. method according to claim 2, it is characterised in that the standard service data is according to being stored in the data base In historical data obtain, or, the standard service data is pre-stored in the data base.
4. method according to claim 3, it is characterised in that according to the historical data being stored in the data base to pre- The standard service data being stored in the data base is modified.
5. air conditioning unit big data analysis method according to claim 2, it is characterised in that:Corresponding display includes The display of trouble unit, air conditioning unit display the reason for break down, and/or the type of alarm command.
6. air conditioning unit big data analysis method according to claim 2, it is characterised in that:The standard service data bag Include air conditioning unit leaving water temperature, local temperature, air conditioning unit average load, current situation, and/or voltage condition.
7. air conditioning unit big data analysis method according to claim 2, it is characterised in that:The air conditioning unit real-time fortune Row data include set sampling time point or fault time point before and after a period of time in the air conditioning unit real time execution number of whole According to.
8. air conditioning unit big data analysis method according to claim 7, it is characterised in that:Described a period of time is 30 points Clock.
9. the air conditioning unit big data analysis method according to any one of claim 1 to 8, it is characterised in that:The data The standard service data for being stored with air conditioning unit in storehouse, the processing system is by the standard service data stored in data base and institute State air conditioning unit real-time running data and be compared analysis, judge air conditioning unit running status whether normal and energy-conservation, and According to judged result, when air conditioning unit running status efficiency is low, adjust instruction is provided, monitoring module is according to adjust instruction bullet Go out the content of corresponding adjust instruction and/or carry out parameters revision.
10. air conditioning unit big data analysis method according to claim 9, it is characterised in that:The processing system is by sky Air conditioning unit leaving water temperature, local environment temperature, air conditioning unit average load and standard fortune in tune unit real-time running data Air conditioning unit leaving water temperature, local environment temperature in row data, air conditioning unit average load compare, when local environment temperature Raising, when air conditioning unit average load is raised, adjust instruction being sent to the monitoring module, the monitoring module refers to according to adjustment Whether order ejection improves the prompting of air conditioning unit leaving water temperature or improves air conditioning unit leaving water temperature.
The 11. air conditioning unit big data analysis methods according to any one of claim 1-8, it is characterised in that:The monitoring Module is display apparatus module.
The 12. air conditioning unit big data analysis methods according to any one of claim 1-8, it is characterised in that:The communication Module is GPRS module.
13. is a kind of using the air conditioning unit of the big data analysis method as described in any one of claim 1 to 12.
CN201610916991.7A 2016-10-21 2016-10-21 A kind of air conditioning unit big data analysis method and air conditioning unit Pending CN106547858A (en)

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CN107461886A (en) * 2017-07-28 2017-12-12 深圳达实智能股份有限公司 A kind of appraisal procedure and device of hospital's PAU cold conveying efficiency
CN109612029A (en) * 2017-10-05 2019-04-12 群光电能科技股份有限公司 Effectiveness Forecast method
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CN108444159B (en) * 2018-03-20 2019-11-08 珠海格力电器股份有限公司 Air conditioning control method and device, air-conditioning
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CN110631177B (en) * 2018-06-25 2021-11-23 青岛海尔空调器有限总公司 Updating method and device for air conditioning system
CN110631176B (en) * 2018-06-25 2021-07-30 重庆海尔空调器有限公司 Updating method and device for air conditioning system
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CN113639452A (en) * 2020-04-27 2021-11-12 青岛海尔空调电子有限公司 Compressor control method for heat exchange system
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CN111861164A (en) * 2020-07-06 2020-10-30 广东德尔智慧工厂科技有限公司 Remote regulation and control analysis method, device and system
CN114193029A (en) * 2020-09-18 2022-03-18 宝山钢铁股份有限公司 Welding machine weld joint pre-evaluation method based on big data analysis model
CN112611082A (en) * 2020-12-11 2021-04-06 珠海格力电器股份有限公司 Air conditioning unit and control method thereof
CN112764384A (en) * 2021-01-05 2021-05-07 易站智联科技(广州)有限公司 Control method, system and storage medium for device management
CN113432243A (en) * 2021-06-29 2021-09-24 河南中烟工业有限责任公司 Intelligent early warning method for running state of air conditioner cabinet
CN114396705A (en) * 2021-12-20 2022-04-26 珠海格力电器股份有限公司 Air conditioner fault detection method and device, electronic equipment and medium
CN114484731A (en) * 2021-12-27 2022-05-13 浙江英集动力科技有限公司 Method and device for diagnosing faults of central air conditioner based on stacking fusion algorithm
CN114484731B (en) * 2021-12-27 2023-05-16 浙江英集动力科技有限公司 Central air conditioner fault diagnosis method and device based on stacking fusion algorithm

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