CN114543406A - Air source heat pump early warning system and method based on Internet of things and air source heat pump - Google Patents
Air source heat pump early warning system and method based on Internet of things and air source heat pump Download PDFInfo
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- CN114543406A CN114543406A CN202210128884.3A CN202210128884A CN114543406A CN 114543406 A CN114543406 A CN 114543406A CN 202210128884 A CN202210128884 A CN 202210128884A CN 114543406 A CN114543406 A CN 114543406A
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 63
- 238000010438 heat treatment Methods 0.000 claims description 21
- 239000003507 refrigerant Substances 0.000 claims description 14
- 230000009467 reduction Effects 0.000 claims description 7
- 230000006855 networking Effects 0.000 claims description 3
- 238000013024 troubleshooting Methods 0.000 abstract description 5
- 230000002035 prolonged effect Effects 0.000 abstract description 2
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
- F25B49/00—Arrangement or mounting of control or safety devices
- F25B49/02—Arrangement or mounting of control or safety devices for compression type machines, plants or systems
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
- F25B30/00—Heat pumps
- F25B30/06—Heat pumps characterised by the source of low potential heat
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
- F25B2500/00—Problems to be solved
- F25B2500/22—Preventing, detecting or repairing leaks of refrigeration fluids
- F25B2500/222—Detecting refrigerant leaks
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Abstract
The invention discloses an air source heat pump early warning system and method based on the Internet of things and an air source heat pump. The air source heat pump early warning system comprises an information acquisition module and an early warning analysis module, wherein the information acquisition module can be connected with the air source heat pump and is used for acquiring the operation data of the air source heat pump in real time; the early warning analysis module is connected with the information acquisition module through the Internet of things, can acquire the operation data of the air source heat pump acquired by the information acquisition module, and analyzes the operation data according to an early warning algorithm to obtain an early warning analysis result. The running state of the air source heat pump can be detected in real time, the state of the air source heat pump is analyzed, and the early warning prompt is automatically generated, so that the troubleshooting efficiency of after-sales service personnel or users is improved, and the service life of the air source heat pump is prolonged. The invention is widely applied to the technical field of air source heat pump early warning.
Description
Technical Field
The invention relates to the field of early warning of air source heat pumps, in particular to an air source heat pump early warning system and method based on the Internet of things and an air source heat pump.
Background
The air source heat pump product is used as a new star in a new energy market, and is widely popular in domestic markets by virtue of the characteristics of high energy efficiency and low power consumption. The air source heat pump has wide application range, is applied to different regions and different climates all over the country, and has various faults under different application working conditions. And the user of the air source heat pump is generally the common people and does not have the capability of assisting in troubleshooting equipment. The after-market maintenance requirements of air source heat pumps are particularly high. The air source heat pump is a civil product, and has particularly high requirement on the stability of the product. Especially in winter, the breakdown of the product can directly affect the daily life of people.
The protection mechanisms of the prior art generally alarm directly to shut down when a unit actually fails. The mechanism of alarm shutdown directly impacts the user experience. And the air source heat pump user generally can not efficiently cooperate with the after-sales personnel to troubleshoot the phenomenon and the fault. The maintenance efficiency of the on-site unit by the after-sales service personnel can be reduced, and even the problem that the same problem appears repeatedly can occur.
Disclosure of Invention
In order to solve at least one technical problem, the invention aims to provide an air source heat pump early warning system and method based on the internet of things and an air source heat pump.
The technical scheme adopted by the invention is as follows:
on one hand, the embodiment of the invention comprises an air source heat pump early warning system based on the internet of things, which comprises:
the information acquisition module is used for acquiring the operating data of the air source heat pump;
and the early warning analysis module is connected with the information acquisition module through the Internet of things and is used for acquiring the operation data, and analyzing the operation data according to an early warning algorithm to obtain an early warning analysis result.
Further, the operation data includes compressor current, fan current and water pump current, and the early warning algorithm includes:
the compressor early warning device is used for acquiring the compressor current and outputting compressor early warning prompt information when the compressor current exceeds a first current threshold and lasts for a first time length;
the fan early warning device is used for acquiring the fan current and outputting fan early warning prompt information when the compressor current exceeds a second current threshold and lasts for a second time length;
and the water pump early warning is used for acquiring the water pump current, and outputting water pump early warning prompt information when the water pump current exceeds a third current threshold and lasts for a third time length.
Further, the operation data includes water flow, and the early warning algorithm includes:
and the heat exchanger filth blockage early warning is used for acquiring the water flow, and when the water flow is lower than the first water flow and lasts for a fourth time length, outputting heat exchanger filth blockage early warning prompt information.
Further, the operation data includes water flow, inlet water temperature and outlet water temperature, and the early warning algorithm includes:
the heating capacity reduction early warning is used for acquiring the water flow, the water inlet temperature and the water outlet temperature, and obtaining a temperature difference according to the water inlet temperature and the water outlet temperature;
obtaining heating capacity according to the temperature difference and the water flow;
and outputting the early warning prompt information of the reduction of the heating capacity when the heating capacity is lower than the first standard heating capacity and lasts for a fifth time length.
Further, the operational data includes high pressure and low pressure, and the warning algorithm includes:
the refrigerant early warning device is used for acquiring high pressure at a first moment and high pressure at a second moment, obtaining a pressure rise value of a sixth time length according to the high pressure at the first moment and the high pressure at the second moment, and outputting refrigerant leakage early warning prompt information when the pressure rise value of the sixth time length is lower than a first pressure threshold value;
and the refrigerant leakage early warning device is used for acquiring the high pressure and the low pressure, and outputting refrigerant leakage early warning prompt information when the ratio of the high pressure to the low pressure is lower than a first ratio threshold.
Further, the operational data includes an exhaust temperature, and the warning algorithm includes:
and the exhaust temperature overhigh early warning device is used for acquiring the exhaust temperature, and outputting exhaust temperature overhigh early warning prompt information when the exhaust temperature is higher than the first temperature threshold and lasts for a seventh time length.
Further, the operation data includes a degree of superheat, and the warning algorithm includes:
and the low superheat degree early warning is used for acquiring the superheat degree, and when the superheat degree is lower than a second temperature threshold value and lasts for an eighth time length, outputting low superheat degree early warning prompt information.
Further, the air source heat pump early warning system based on the internet of things further comprises:
determining early warning levels according to the early warning analysis result, wherein the early warning levels are classified into high-level early warning, middle-level early warning and low-level early warning;
and executing corresponding early warning actions according to the early warning level.
On the other hand, the embodiment of the invention also comprises an air source heat pump early warning method, which comprises the following steps:
acquiring operation data of the air source heat pump;
and analyzing the operation data according to the early warning algorithm to obtain an early warning analysis result.
On the other hand, the embodiment of the invention also comprises an air source heat pump, wherein the air source heat pump early warning system based on the Internet of things is included.
The invention has the beneficial effects that: according to the air source heat pump early warning system based on the Internet of things, the running data on the air source heat pump unit can be collected through the Internet of things, the data can be stored and recorded on the cloud platform server, potential problems of the unit can be analyzed and summarized through an early warning algorithm, an early warning analysis result is automatically generated and is prompted on the platform, and after-sales service personnel can perform troubleshooting and maintenance on the unit with the possible problems in advance and reduce the influence of the problems on customers through the prompt of the early warning system.
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Fig. 1 is a structural diagram of an air source heat pump early warning system based on the internet of things according to an embodiment of the invention;
fig. 2 is a flow chart of an air source heat pump early warning method based on the internet of things according to the embodiment of the invention.
Detailed Description
The embodiment of the invention provides an air source heat pump early warning system based on the Internet of things, which comprises an information acquisition module and an early warning analysis module, wherein the information acquisition module is used for acquiring the operation data of an air source heat pump, as shown in FIG. 1; the early warning analysis module is connected with the information acquisition module through the Internet of things and used for acquiring operation data of the air source heat pump, the early warning model of the air source heat pump is designed by combining an air source heat pump unit system according to typical fault contents of the past air source heat pump, the operation data of the air source heat pump acquired by the information acquisition module is input into the early warning model, and an early warning algorithm in the early warning model analyzes the operation data to obtain an early warning analysis result. The data that can regularly gather on the air source heat pump set by thing networking module to realize the storage record of data on the cloud platform server, gather the problem of unit potential through the early warning algorithm, the early warning analysis result of the different early warning grades of automatic generation, and show on the platform. The user can inquire the running state of the air source heat pump through the Internet of things platform in real time, the running parameters of the air source heat pump are displayed in the Internet of things platform in real time, the user can be reminded of overhauling when abnormal data occur, troubleshooting efficiency is improved, and the service life of the air source heat pump is prolonged.
As shown in fig. 2, the internet of things module can be arranged to acquire data acquired by the air source heat pump unit at regular time, the data can be stored and recorded on the cloud platform server, potential problems of the unit can be analyzed and summarized through the early warning algorithm module, early warning information of different early warning levels can be automatically generated, and the early warning information can be prompted on the platform.
Wherein, according to gathering the more typical trouble content of past air source heat pump to the early warning model of air source heat pump who combines air source heat pump set system design includes: the system comprises a compressor early warning algorithm, a fan early warning algorithm, a water pump early warning algorithm, a heat exchanger filth blockage early warning algorithm, a heating capacity reduction early warning algorithm, a refrigerant leakage early warning algorithm, an exhaust temperature early warning algorithm and a low superheat degree early warning algorithm. Different fault contents are divided into different algorithms, so that the fault aspect can be clearly displayed, the fault troubleshooting efficiency is improved, and a user can conveniently and simply adjust and repair the fault according to the analysis result obtained by the algorithm.
The early warning algorithm of the compressor comprises the following steps: the information acquisition module acquires the continuous running current of a compressor of the air source heat pump unit, inputs the continuous running current into the early warning model, prompts the early warning of the compressor when the running current of the compressor exceeds an early warning preset value and lasts for 10 minutes, and records the unit state during early warning. The current when the operating current of air source heat pump unit compressor breaks down sets up the early warning default according to actual conditions, generally surpasss the default and lasts the condition that can lead to the compressor to break down or reduce life after the certain time when the operating current of compressor, and the user can pass through internet of things with air source heat pump by user terminal, and when the compressor early warning suggestion appears, the thing networking platform can send the compressor early warning suggestion to user terminal, and the suggestion user overhauls.
The fan early warning algorithm comprises the following steps: the information acquisition module acquires continuous running current of a fan of the air source heat pump unit, inputs the continuous running current into the early warning model, prompts early warning of the fan when the running current of the fan exceeds an early warning preset value and lasts for 10 minutes, and records the unit state during early warning. The early warning default is set according to the current when the running current of the air source heat pump unit fan breaks down in actual conditions, generally, when the running current of the fan exceeds the default and lasts for a certain time, the fan breaks down or the service life is shortened, a user can use the terminal to be connected with the air source heat pump through the Internet of things, when the fan early warning prompt appears, the Internet of things platform can send the fan early warning prompt to the user terminal, and the user is prompted to overhaul.
The water pump early warning algorithm comprises the following steps: the information acquisition module acquires continuous running current of a water pump of the air source heat pump unit, inputs the continuous running current into the early warning model, prompts early warning of the water pump when the running current of the water pump exceeds an early warning preset value and lasts for 10 minutes, and records the unit state during early warning. According to actual conditions, the current when the running current of the air source heat pump unit water pump breaks down sets an early warning preset value, the running current of the water pump exceeds the preset value and lasts for a certain time, the water pump can break down or the service life of the water pump can be reduced, a user can use the terminal to be connected with the air source heat pump through the Internet of things, when the early warning prompt of the water pump appears, the Internet of things platform can send a water pump early warning prompt to the user terminal, and the user is prompted to overhaul.
The heat exchanger filth blockage early warning algorithm comprises the following steps: the information acquisition module acquires water flow of the air source heat pump unit, inputs the water flow into the early warning model, and prompts early warning of filth blockage of the heat exchanger when the water flow of the system is lower than standard water flow SQ 70% and lasts for 2 minutes, and records the unit state during early warning. According to the practical situation, the early warning preset value is set according to the water flow when the water flow of the heat exchanger of the air source heat pump unit system is dirty and blocked, generally, when the water flow of the air source heat pump system is lower than a certain water flow, the water flow is possibly caused by the fact that the heat exchanger is dirty and blocked, a user can use the terminal to be connected with the air source heat pump through the Internet of things, and when the early warning prompt of the dirty and blocked of the heat exchanger appears, the Internet of things platform can send the early warning prompt of the dirty and blocked of the heat exchanger to the user terminal to prompt the user to overhaul.
Heating capacity reduction early warning algorithm: the information acquisition module acquires the water flow, the water outlet temperature and the water inlet temperature of the air source heat pump unit, the temperature difference is obtained according to the water outlet temperature and the water inlet temperature, the heating capacity is obtained according to the temperature difference and the water flow, when the system does not prompt that the heat exchanger is dirty and blocked, the heating capacity is lower than the standard heating capacity SP by 70 percent and lasts for 30 minutes, the early warning of insufficient heating capacity is prompted, and the unit state during the early warning is recorded. According to the heating capacity data setting early warning default when the heating capacity of air source heat pump unit system descends in actual conditions, the user can use the terminal to pass through internet of things with air source heat pump, and when the heating capacity descends the early warning and prompts, the internet of things platform can send the heating capacity to the user terminal and descend the early warning and prompt the user to overhaul.
The refrigerant leakage early warning algorithm comprises the following steps: the information acquisition module acquires high-pressure and low-pressure when a compressor of the air source heat pump unit is started, delays for 2 minutes after the compressor is started, and if the rising value of the high-pressure is lower than a preset value SPh, the unit is considered to have refrigerant leakage; or when the ratio of the high pressure to the low pressure is lower than the preset ratio Pdif in the running process of the unit, the unit is considered to have refrigerant leakage, and the refrigerant leakage early warning is prompted. The unit pipelines need to be overhauled, and the unit state during early warning is recorded.
An exhaust gas over-temperature early warning algorithm: the information acquisition module acquires the exhaust temperature of the air source heat pump unit, inputs the exhaust temperature into the early warning model, and prompts early warning of overhigh exhaust temperature when the exhaust temperature exceeds the preset early warning exhaust temperature and lasts for 10 minutes. The control parameters of the unit need to be adjusted, damage caused by high temperature of the compressor for a long time is avoided, and the unit state during early warning is recorded. The preset early warning exhaust temperature and duration are set according to actual conditions.
And (3) low superheat degree early warning algorithm: the information acquisition module acquires the superheat degree of the air source heat pump unit, inputs the superheat degree into the early warning model, and prompts early warning of low superheat degree when the superheat degree is lower than a low superheat degree preset value and the duration time is longer than 5 minutes. The unit needs to be inspected and overhauled, the compressor can be damaged due to long-time low superheat degree, and the unit state during early warning is recorded. And setting a low superheat degree preset value and duration according to actual conditions.
It should be further noted that the potential problems of the unit can be analyzed and summarized through the early warning algorithm, and early warning information of different early warning levels can be automatically generated, wherein the early warning levels are divided into high, medium and low. The early warning level is high, which indicates that the equipment is abnormal and needs to be maintained in time; in the early warning level, the fact that the equipment is abnormal possibly indicates that the equipment needs to be overhauled on site; the early warning level is low, the running state of the equipment is represented to be bad, the equipment is enabled to run normally through parameter optimization, and the running parameters of the equipment unit can be optimized remotely through the Internet of things. Setting the early warning level of the compressor to be high; setting the early warning level of the fan to be high; setting the early warning level of the water pump to be high; the early warning of the filth blockage of the heat exchanger is set to be low in early warning level; the early warning of the reduction of the heating capacity is set to be low in early warning level; setting the refrigerant leakage early warning to be in an early warning level; setting the exhaust temperature early warning to be in an early warning level; and setting the low superheat degree early warning to be low in early warning level.
The invention is not limited to the typical early warning obtained by summarizing the typical fault content of the past air source heat pump in the embodiment, and can be expanded on the idea of the invention to collect the operation data of more air source heat pumps and obtain early warning models and algorithms in more states.
On the other hand, the embodiment of the invention also comprises an air source heat pump early warning method, which comprises the steps of obtaining the operation data of the air source heat pump, and analyzing the operation data of the air source heat pump according to the early warning algorithm in the embodiment to obtain an early warning analysis result.
On the other hand, the embodiment of the invention also comprises an air source heat pump, wherein the air source heat pump early warning system based on the internet of things in the embodiment is included.
It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it can be directly fixed or connected to the other feature or indirectly fixed or connected to the other feature. Furthermore, the descriptions of upper, lower, left, right, etc. used in the present disclosure are only relative to the mutual positional relationship of the constituent parts of the present disclosure in the drawings. As used in this disclosure, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. In addition, unless defined otherwise, all technical and scientific terms used in this example have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in the description of the embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this embodiment, the term "and/or" includes any combination of one or more of the associated listed items.
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element of the same type from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of the present disclosure. The use of any and all examples, or exemplary language ("e.g.," such as "or the like") provided with this embodiment is intended merely to better illuminate embodiments of the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.
It should be recognized that embodiments of the present invention can be realized and implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with the computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, according to the methods and figures described in the detailed description. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, operations of processes described in this embodiment can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described in this embodiment (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable interface, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described in this embodiment includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein.
A computer program can be applied to input data to perform the functions described in the present embodiment to convert the input data to generate output data that is stored to a non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
The above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention as long as the technical effects of the present invention are achieved by the same means. The invention is capable of other modifications and variations in its technical solution and/or its implementation, within the scope of protection of the invention.
Claims (10)
1. The utility model provides an air source heat pump early warning system based on thing networking which characterized in that includes:
the information acquisition module is used for acquiring the operating data of the air source heat pump;
and the early warning analysis module is connected with the information acquisition module through the Internet of things and is used for acquiring the operation data, and analyzing the operation data according to an early warning algorithm to obtain an early warning analysis result.
2. The internet of things-based air source heat pump early warning system of claim 1, wherein the operation data comprises compressor current, fan current and water pump current, and the early warning algorithm comprises:
the compressor early warning device is used for acquiring the compressor current and outputting compressor early warning prompt information when the compressor current exceeds a first current threshold and lasts for a first time length;
the fan early warning device is used for acquiring the fan current and outputting fan early warning prompt information when the compressor current exceeds a second current threshold and lasts for a second time length;
and the water pump early warning is used for acquiring the water pump current, and outputting water pump early warning prompt information when the water pump current exceeds a third current threshold and lasts for a third time length.
3. The internet of things-based air source heat pump early warning system of claim 1, wherein the operational data comprises water flow, and the early warning algorithm comprises:
and the heat exchanger filth blockage early warning is used for acquiring the water flow, and when the water flow is lower than the first water flow and lasts for a fourth time length, outputting heat exchanger filth blockage early warning prompt information.
4. The internet of things-based air source heat pump early warning system of claim 1, wherein the operation data comprises water flow, inlet water temperature and outlet water temperature, and the early warning algorithm comprises:
the heating capacity reduction early warning is used for acquiring the water flow, the water inlet temperature and the water outlet temperature and obtaining a temperature difference according to the water inlet temperature and the water outlet temperature;
obtaining heating capacity according to the temperature difference and the water flow;
and outputting the early warning prompt information of the reduction of the heating capacity when the heating capacity is lower than the first standard heating capacity and lasts for a fifth time length.
5. The internet of things-based air source heat pump early warning system of claim 1, wherein the operating data comprises a high pressure and a low pressure, and the early warning algorithm comprises:
the refrigerant early warning device is used for acquiring high pressure at a first moment and high pressure at a second moment, obtaining a pressure rise value of a sixth time length according to the high pressure at the first moment and the high pressure at the second moment, and outputting refrigerant leakage early warning prompt information when the pressure rise value of the sixth time length is lower than a first pressure threshold value;
and the refrigerant leakage early warning device is used for acquiring the high pressure and the low pressure, and outputting refrigerant leakage early warning prompt information when the ratio of the high pressure to the low pressure is lower than a first ratio threshold.
6. The internet of things-based air source heat pump early warning system of claim 1, wherein the operating data comprises an exhaust temperature, and the early warning algorithm comprises:
and the exhaust temperature overhigh early warning device is used for acquiring the exhaust temperature, and outputting exhaust temperature overhigh early warning prompt information when the exhaust temperature is higher than the first temperature threshold and lasts for a seventh time length.
7. The internet of things-based air source heat pump early warning system as claimed in claim 1, wherein the operation data comprises superheat degree, and the early warning algorithm comprises:
and the low superheat degree early warning is used for acquiring the superheat degree, and when the superheat degree is lower than a second temperature threshold value and lasts for an eighth time length, outputting low superheat degree early warning prompt information.
8. The internet of things-based air source heat pump early warning system according to any one of claims 1-7, further comprising:
determining early warning levels according to the early warning analysis result, wherein the early warning levels are classified into high-level early warning, middle-level early warning and low-level early warning;
and executing corresponding early warning actions according to the early warning level.
9. An early warning method for an air source heat pump is characterized by comprising the following steps:
acquiring operation data of the air source heat pump;
the early warning algorithm according to any one of claims 1-7, analyzing the operational data to obtain an early warning analysis result.
10. An air-source heat pump, characterized by comprising the early warning system of any one of claims 1-8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114838456A (en) * | 2022-07-04 | 2022-08-02 | 浙江大学滨海产业技术研究院 | Multi-air-conditioning equipment early warning system and method based on dynamic rules and asynchronous calculation |
| CN115682468A (en) * | 2022-11-07 | 2023-02-03 | 鼎恒(烟台)科技发展有限公司 | Air source heat pump unit intelligence operation and maintenance management and control system based on data analysis |
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| CN115682468B (en) * | 2022-11-07 | 2023-04-14 | 鼎恒(烟台)科技发展有限公司 | Air source heat pump set intelligence operation and maintenance management and control system based on data analysis |
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