CN113449977B - Heat recycling system of air compression station - Google Patents
Heat recycling system of air compression station Download PDFInfo
- Publication number
- CN113449977B CN113449977B CN202110695842.3A CN202110695842A CN113449977B CN 113449977 B CN113449977 B CN 113449977B CN 202110695842 A CN202110695842 A CN 202110695842A CN 113449977 B CN113449977 B CN 113449977B
- Authority
- CN
- China
- Prior art keywords
- air compressor
- heat
- water
- abnormal
- temperature
- 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
- 238000004064 recycling Methods 0.000 title claims abstract description 32
- 230000006835 compression Effects 0.000 title claims description 8
- 238000007906 compression Methods 0.000 title claims description 8
- 238000001514 detection method Methods 0.000 claims abstract description 85
- 238000004364 calculation method Methods 0.000 claims abstract description 9
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 139
- 238000011084 recovery Methods 0.000 claims description 85
- 230000002159 abnormal effect Effects 0.000 claims description 83
- 239000002918 waste heat Substances 0.000 claims description 48
- 238000000034 method Methods 0.000 claims description 31
- 239000007789 gas Substances 0.000 claims description 17
- 238000004519 manufacturing process Methods 0.000 claims description 16
- 239000000428 dust Substances 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 11
- 238000005259 measurement Methods 0.000 claims description 10
- 238000003860 storage Methods 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 6
- JEGUKCSWCFPDGT-UHFFFAOYSA-N h2o hydrate Chemical compound O.O JEGUKCSWCFPDGT-UHFFFAOYSA-N 0.000 claims description 4
- 238000010438 heat treatment Methods 0.000 claims description 4
- 230000002093 peripheral effect Effects 0.000 description 5
- 230000005611 electricity Effects 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000017525 heat dissipation Effects 0.000 description 1
- 239000008236 heating water Substances 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B39/00—Component parts, details, or accessories, of pumps or pumping systems specially adapted for elastic fluids, not otherwise provided for in, or of interest apart from, groups F04B25/00 - F04B37/00
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F28—HEAT EXCHANGE IN GENERAL
- F28D—HEAT-EXCHANGE APPARATUS, NOT PROVIDED FOR IN ANOTHER SUBCLASS, IN WHICH THE HEAT-EXCHANGE MEDIA DO NOT COME INTO DIRECT CONTACT
- F28D21/00—Heat-exchange apparatus not covered by any of the groups F28D1/00 - F28D20/00
- F28D21/0001—Recuperative heat exchangers
- F28D21/0014—Recuperative heat exchangers the heat being recuperated from waste air or from vapors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/30—Administration of product recycling or disposal
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W90/00—Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Mechanical Engineering (AREA)
- Quality & Reliability (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Thermal Sciences (AREA)
- Data Mining & Analysis (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses a heat recycling system of an air compressor station, which relates to the technical field of heat recycling and solves the problems that the running efficiency of an air compressor is reduced due to the fact that the redundant heat cannot be numerically calculated in the prior art, running information of the air compressor is analyzed through a heat measuring unit, heat generated by the running of the air compressor is measured, a heat detection coefficient RLi of the air compressor is obtained through a formula, if the heat detection coefficient RLi of the air compressor is larger than or equal to a heat detection coefficient threshold value, the heat of the air compressor needs to be measured, a temperature value of internal air before the air compressor runs is obtained, the temperature of the internal air of the air compressor at present is obtained after the air compressor runs, and heat Qi released when the air compressor runs is obtained through the formula; the heat of the air compressor is detected, and the numerical calculation is carried out on the redundant heat, so that the accuracy of heat recycling is improved, and the situation that the recycling time is improper is prevented, and the running efficiency of the air compressor is reduced.
Description
Technical Field
The invention relates to the technical field of heat recycling, in particular to a heat recycling system of an air compression station.
Background
Compressed air is widely applied to various fields of industrial production, and according to statistics, the electricity consumption of an air compressor accounts for 9.4% of the national electricity consumption. Only 10% of the electric energy consumed by the air compressor is converted into compressed air energy, and the rest 90% of the electric energy is converted into various forms of heat energy to be wasted. In the long-term continuous operation process of the air compressor, the air compressor is heated suddenly by strongly compressing the air, so that high-temperature heat is generated. The heat of the high-temperature oil/gas is 75% of the input power of the compressor, the temperature is between 80 and 100 ℃, and the heat is finally exhausted to the atmosphere through the heat dissipation system of the air compressor.
In the prior art, numerical calculation cannot be carried out on the redundant heat, so that the recovery time is not appropriate, and the operation efficiency of the air compressor is reduced.
Disclosure of Invention
The invention aims to provide an air compressor station heat recycling system, wherein operation information of an air compressor is analyzed through a heat measuring unit, heat generated by the operation of the air compressor is measured, a heat detection coefficient RLi of the air compressor is obtained through a formula, if the heat detection coefficient RLi of the air compressor is larger than or equal to a heat detection coefficient threshold value, the heat of the air compressor is judged to be measured, after a manager receives a heat measurement signal, the heat generated by the air compressor is measured, a temperature value of internal air before the operation of the air compressor is obtained and is marked as Ti0, the temperature of the internal air of the air compressor is obtained after the operation of the air compressor and is marked as specific heat Ti1, then under the current Ti1 temperature, the constant pressure capacity of the air is obtained, and the heat Qi released by the operation of the air compressor is obtained through the formula; the heat of the air compressor is detected, and the numerical calculation is carried out on the redundant heat, so that the accuracy of heat recycling is improved, and the situation that the recycling time is improper is prevented, and the running efficiency of the air compressor is reduced.
The purpose of the invention can be realized by the following technical scheme:
a heat recycling system of an air compression station comprises a cloud management platform, a heat measuring unit, a recycling unit, an environment detection unit, an efficiency detection unit, a registration unit and a database;
the heat measuring unit is used for analyzing the operation information of the air compressor, measuring the heat generated by the operation of the air compressor, wherein the operation information of the air compressor comprises temperature data, duration data and power data, the temperature data is the difference value between the temperature and the external temperature in the operation process of the air compressor, the duration data is the working duration of the continuous operation of the air compressor, the power data is the ratio of the operation power of the air compressor to the rated operation power, the air compressor is marked as i, i is 1, 2, … …, n and n is a positive integer, and the specific analysis and measurement process is as follows:
step S1: acquiring a difference value between the temperature of the air compressor in the operation process and the external temperature, and marking the difference value between the temperature of the air compressor in the operation process and the external temperature as CZi;
step S2: acquiring the continuous operation working time of the air compressor, and marking the continuous operation working time of the air compressor as SCi;
step S3: acquiring the ratio of the operating power of the air compressor to the rated operating power, and marking the ratio of the operating power of the air compressor to the rated operating power as BZi;
step S4: acquiring a heat detection coefficient RLi of the air compressor by using a formula RLi ═ beta (CZi × a1+ SCi × a2+ BZi × a3), wherein a1, a2 and a3 are proportional coefficients, a1 is greater than a2 and greater than a3 is greater than 0, and beta is an error correction factor and takes the value of 2.032125;
step S5: comparing the heat detection coefficient RLi of the air compressor with a heat detection coefficient threshold value:
if the heat detection coefficient RLi of the air compressor is larger than or equal to the heat detection coefficient threshold value, judging that the heat of the air compressor needs to be measured, generating a heat measurement signal and sending the heat measurement signal to a mobile phone terminal of a manager;
if the heat detection coefficient RLi of the air compressor is smaller than the heat detection coefficient threshold value, judging that the heat of the air compressor does not need to be measured, generating a heat undetermined signal and sending the heat undetermined signal to a mobile phone terminal of a manager;
step S6: after receiving the heat measuring signal, a manager measures the heat generated by the air compressor, obtains a temperature value of the internal air before the air compressor operates, marks the temperature value as Ti0, obtains the current temperature of the internal air of the air compressor after the air compressor operates, marks the temperature value as Ti1, obtains the constant-pressure specific heat capacity of the air at the current Ti1 temperature, marks the constant-pressure specific heat capacity as Ci, and obtains the heat Qi released when the air compressor operates through a formula Qi which is Ci × m × (Ti1-Ti0), wherein m represents the air quality inside the air compressor; and then, transmitting the heat Qi released when the air compressor operates to the cloud management platform.
Further, after receiving heat Qi released when the press operates, the cloud management platform generates a heat recovery signal and sends the heat recovery signal to the recycling unit, and after receiving the heat recovery signal, the recycling unit recycles the heat, and the specific recycling process is as follows:
step SS 1: acquiring the initial temperature of water in the water tank, marking the initial temperature of the water as T0, and then setting the heated water temperature by a manager according to the use mode of the water, and marking the heated water temperature as T1;
step SS 2: obtaining the specific heat capacity of the water and marking the specific heat capacity of the water as CWater (W)Obtaining the volume value of the water tank and marking the volume value of the water tank as VWater (W)Acquiring the mass of water in the water tank according to the volume value of the water tank, namely obtaining the mass of water in the water tank according to the formula mWater (W)＝α(ρvWater (W)) Wherein rho is the density of water, alpha is an error correction factor, and the value is 2.32562;
step SS 3: the heat Qi and the specific heat CWater (W)Mass m of waterWater (W)And the starting temperature T0 of water into the formula, and calculating by the heat calculation formula Qi ═ CWater (W)×mWater (W)Calculating the temperature T2 at which the heat Qi can heat the water by the aid of the heat quantity Qi (T2-T0), then comparing the temperature T2 of the water with a set water temperature T1, stopping heating the water tank if the temperature T2 of the water is larger than or equal to the set water temperature T1, generating a recovery completion signal, and sending the recovery completion signal to a cloud management platform; if the temperature T2 of the water is less than the set water temperature T1, the water tank is continuously heated.
Further, after receiving the recovery completion signal, the cloud management platform generates an efficiency detection signal and sends the efficiency detection signal to the efficiency detection unit, after receiving the efficiency detection signal, the efficiency detection unit analyzes the efficiency information of the air compressor, so as to detect the heat recovery efficiency of the air compressor, the efficiency information of the air compressor comprises gas production data, electric quantity data and hot water data, the gas production data is a gas production difference value before and after waste heat recovery of the air compressor, the electric quantity data saves the number of degrees for the electric quantity of the air compressor after waste heat recovery, the hot water data is the ton of hot water production of the air compressor after waste heat recovery, and the specific analysis and detection process is as follows:
step T1: acquiring a gas production difference value before and after waste heat recovery of the air compressor, and marking the gas production difference value before and after waste heat recovery of the air compressor as CQi;
step T2: acquiring the electric quantity saving degree of the air compressor after waste heat recovery, and marking the electric quantity saving degree of the air compressor after waste heat recovery as DSi;
step T3: acquiring the tonnage of hot water produced after waste heat recovery of an air compressor, and marking the tonnage of hot water produced after waste heat recovery of the air compressor as RSi;
step T4: by the formula
Obtaining an efficiency coefficient JCi of waste heat recovery of the air compressor, wherein b1, b2 and b3 are proportional coefficients, and b1 is more than b2 is more than b3 is more than 0;
step T5: comparing an efficiency coefficient JCi of waste heat recovery of the air compressor with an efficiency coefficient threshold:
if the efficiency coefficient JCi of the air compressor for waste heat recovery is larger than or equal to the efficiency coefficient threshold value, judging that the efficiency of the air compressor for waste heat recovery is high, generating a recovery efficiency normal signal and sending the recovery efficiency normal signal to the cloud management platform;
if the efficiency coefficient JCi of the air compressor for waste heat recovery is less than the efficiency coefficient threshold value, judging that the efficiency of the air compressor for waste heat recovery is low, marking the corresponding air compressor as an abnormal air compressor, simultaneously generating a recovery efficiency abnormal signal and sending the recovery efficiency abnormal signal and the abnormal air compressor to the cloud management platform together.
Further, after the cloud management platform receives the recovery efficiency abnormal signal and the abnormal air compressor, generate an environment detection signal and send the environment detection signal to the environment detection unit, after the environment detection unit receives the environment detection signal, the ambient environment information of the abnormal air compressor is analyzed, thereby the ambient environment of the abnormal air compressor is detected, the ambient environment information of the abnormal air compressor comprises dust data, pressure data and humidity data, the dust data is the dust content of the ambient environment in the operation process of the abnormal air compressor, the pressure data is the difference value of the internal and external pressures in the air storage tank of the abnormal air compressor, the humidity data is the average humidity of the ambient environment of the abnormal air compressor all day, the abnormal air compressor is marked as o, o is 1, 2, … …, m and m is a positive integer, and the specific analysis and detection process is as follows:
step TT 1: acquiring the dust content of the surrounding environment in the running process of the abnormal air compressor, and marking the dust content of the surrounding environment in the running process of the abnormal air compressor as FCo;
step TT 2: acquiring an internal and external pressure difference value of an air storage tank of the abnormal air compressor, and marking the internal and external pressure difference value of the air storage tank of the abnormal air compressor as YLo;
step TT 3: acquiring the average humidity of the surrounding environment of the abnormal air compressor all day, and marking the average humidity of the surrounding environment of the abnormal air compressor all day as SDo;
step TT 4: by the formula HJo ═ (FCo xs 1+ YLo xs 2+ SDo xs 3) es1+s2+s3Obtaining an environment detection coefficient HJo of the abnormal air compressor, wherein s1, s2 and s3 are proportional coefficients, s1 is more than s2 is more than s3 is more than 0, and e is a natural constant;
step TT 5: comparing the environment detection coefficient HJo of the abnormal air compressor with an environment detection coefficient threshold value:
if the environment detection coefficient HJo of the abnormal air compressor is larger than or equal to the environment detection coefficient threshold value, judging that the surrounding environment of the abnormal air compressor is abnormal, generating an environment abnormal signal and sending the environment abnormal signal to a mobile phone terminal of a maintainer;
and if the environment detection coefficient HJo of the abnormal air compressor is less than the environment detection coefficient threshold value, judging that the surrounding environment of the abnormal air compressor is normal, generating an equipment abnormal signal and sending the equipment abnormal signal to a mobile phone terminal of a maintainer.
Further, the registration login unit is used for the manager and the maintainer to submit the manager information and the maintainer information through the mobile phone terminal, and the manager information and the maintainer information which are successfully registered are sent to the database to be stored, the manager information comprises the name, the age, the time of entry and the mobile phone number of the real name authentication of the manager, and the maintainer information comprises the name, the age, the time of entry and the mobile phone number of the real name authentication of the person.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, the operation information of the air compressor is analyzed by the heat measuring unit, the heat generated by the operation of the air compressor is measured, obtaining the heat detection coefficient RLi of the air compressor through a formula, if the heat detection coefficient RLi of the air compressor is more than or equal to the heat detection coefficient threshold value, then the heat of the air compressor needs to be measured, after the manager receives the heat measuring signal, measuring the heat generated by the air compressor to obtain the temperature value of the air inside the air compressor before the air compressor operates, and is marked as Ti0, the air compressor obtains the current air temperature inside the air compressor after running, and labeled as Ti1, then at the current Ti1 temperature, the constant pressure specific heat capacity of air is taken, and labeled as Ci, acquiring heat Qi released by the air compressor during operation through a formula of Qi, Ci x m x (Ti1-Ti0), and then sending the heat Qi released by the air compressor during operation to a cloud management platform; the heat of the air compressor is detected, and the numerical calculation is carried out on the redundant heat, so that the accuracy of heat recycling is improved, and the reduction of the running efficiency of the air compressor caused by improper recycling time is prevented;
2. according to the invention, after receiving a heat recovery signal, a recovery unit recovers and utilizes heat to obtain the initial temperature of water in the water tank, the initial temperature of the water is marked as T0, and then a manager sets the heated water temperature according to the use mode of the water and marks the heated water temperature as T1; obtaining the specific heat capacity of the water and marking the specific heat capacity of the water as CWater (W)Obtaining the volume value of the water tank and marking the volume value of the water tank as VWater (W)Acquiring the quality of water in the water tank according to the volume value of the water tank, and acquiring the heat Qi and the specific heat CWater (W)Mass m of waterWater (W)Andsubstituting the initial temperature T0 of water into a formula for calculation, calculating the temperature T2 of heat Qi capable of heating water through a heat calculation formula, then comparing the temperature T2 of the water with the set water temperature T1, if the temperature T2 of the water is not less than the set water temperature T1, stopping heating the water tank, generating a recovery completion signal and sending the recovery completion signal to a cloud management platform; if the temperature T2 of the water is less than the set water temperature T1, the water tank is continuously heated; the waste heat is recycled, so that the consumption of resources is saved, and meanwhile, the water temperature is increased to the set temperature through the waste heat, so that the use quality of a user is improved, and the efficiency of waste heat recycling is enhanced.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the heat recycling system for the air compression station includes a cloud management platform, a heat measuring unit, a recycling unit, an environment detecting unit, an efficiency detecting unit, a registration unit, and a database;
the registration login unit is used for submitting manager information and maintainer information through mobile phone terminals by managers and maintainers, and sending the manager information and the maintainer information which are successfully registered to the database for storage, wherein the manager information comprises the name, the age, the time of entry and the mobile phone number of real-name authentication of the manager, and the maintainer information comprises the name, the age, the time of entry and the mobile phone number of real-name authentication of the maintainer;
the heat survey unit is used for analyzing the operation information of air compressor machine, survey the heat that the air compressor machine operation produced, the operation information of air compressor machine includes temperature data, length of time data and power data, temperature data is the temperature and the ambient temperature difference in the air compressor machine operation, length of time data is the operating duration of air compressor machine continuous operation, power data is the ratio of air compressor machine operating power and rated operating power, mark the air compressor machine as i, i is 1, 2, … …, n, n is the positive integer, the specific analysis survey process is as follows:
step S1: acquiring a difference value between the temperature of the air compressor in the operation process and the external temperature, and marking the difference value between the temperature of the air compressor in the operation process and the external temperature as CZi;
step S2: acquiring the continuous operation working time of the air compressor, and marking the continuous operation working time of the air compressor as SCi;
step S3: acquiring the ratio of the operating power of the air compressor to the rated operating power, and marking the ratio of the operating power of the air compressor to the rated operating power as BZi;
step S4: acquiring a heat detection coefficient RLi of the air compressor by using a formula RLi ═ beta (CZi × a1+ SCi × a2+ BZi × a3), wherein a1, a2 and a3 are proportional coefficients, a1 is greater than a2 and greater than a3 is greater than 0, and beta is an error correction factor and takes the value of 2.032125;
step S5: comparing the heat detection coefficient RLi of the air compressor with a heat detection coefficient threshold value:
if the heat detection coefficient RLi of the air compressor is larger than or equal to the heat detection coefficient threshold value, judging that the heat of the air compressor needs to be measured, generating a heat measurement signal and sending the heat measurement signal to a mobile phone terminal of a manager;
if the heat detection coefficient RLi of the air compressor is smaller than the heat detection coefficient threshold value, judging that the heat of the air compressor does not need to be measured, generating a heat undetermined signal and sending the heat undetermined signal to a mobile phone terminal of a manager;
step S6: after receiving the heat measuring signal, a manager measures the heat generated by the air compressor, obtains a temperature value of the internal air before the air compressor operates, marks the temperature value as Ti0, obtains the current temperature of the internal air of the air compressor after the air compressor operates, marks the temperature value as Ti1, obtains the constant-pressure specific heat capacity of the air at the current Ti1 temperature, marks the constant-pressure specific heat capacity as Ci, and obtains the heat Qi released when the air compressor operates through a formula Qi which is Ci × m × (Ti1-Ti0), wherein m represents the air quality inside the air compressor; then, transmitting heat Qi released when the air compressor operates to a cloud management platform;
after the cloud management platform receives the heat Qi released when the press operates, heat recovery signals are generated and sent to the recycling unit, and after the recycling unit receives the heat recovery signals, the heat is recycled, and the specific recycling process is as follows:
step SS 1: acquiring the initial temperature of water in the water tank, marking the initial temperature of the water as T0, and then setting the heated water temperature by a manager according to the use mode of the water, and marking the heated water temperature as T1;
step SS 2: obtaining the specific heat capacity of the water and marking the specific heat capacity of the water as CWater (W)Obtaining the volume value of the water tank and marking the volume value of the water tank as VWater (W)Acquiring the mass of water in the water tank according to the volume value of the water tank, namely obtaining the mass of water in the water tank according to the formula mWater (W)＝α(ρvWater (W)) Wherein rho is the density of water, alpha is an error correction factor, and the value is 2.32562;
step SS 3: the heat Qi and the specific heat CWater (W)Mass m of waterWater (W)And the starting temperature T0 of water into the formula, and calculating by the heat calculation formula Qi ═ CWater (W)×mWater (W)Calculating the temperature T2 at which the heat Qi can heat the water by the aid of the heat quantity Qi (T2-T0), then comparing the temperature T2 of the water with a set water temperature T1, stopping heating the water tank if the temperature T2 of the water is larger than or equal to the set water temperature T1, generating a recovery completion signal, and sending the recovery completion signal to a cloud management platform; if the temperature T2 of the water is less than the set water temperature T1, the water tank is continuously heated;
after the cloud management platform receives the recovery completion signal, generate efficiency detection signal and send efficiency detection signal to efficiency detecting element, after efficiency detecting element received efficiency detection signal, the efficiency information to the air compressor machine carries out the analysis, thereby detect the heat recovery efficiency to the air compressor machine, the efficiency information of air compressor machine includes the gas production data, electric quantity data and hot water data, the gas production difference before and after the gas production data carries out waste heat recovery for the air compressor machine, electric quantity data saves the number of degrees for the electric quantity of air compressor machine after carrying out waste heat recovery, hot water data produces hydrothermal ton after carrying out waste heat recovery for the air compressor machine, concrete analysis testing process is as follows:
step T1: acquiring a gas production difference value before and after waste heat recovery of the air compressor, and marking the gas production difference value before and after waste heat recovery of the air compressor as CQi;
step T2: acquiring the electric quantity saving degree of the air compressor after waste heat recovery, and marking the electric quantity saving degree of the air compressor after waste heat recovery as DSi;
step T3: acquiring the tonnage of hot water produced after waste heat recovery of an air compressor, and marking the tonnage of hot water produced after waste heat recovery of the air compressor as RSi;
step T4: by the formula
Obtaining an efficiency coefficient JCi of waste heat recovery of the air compressor, wherein b1, b2 and b3 are proportional coefficients, and b1 is more than b2 is more than b3 is more than 0;
step T5: comparing an efficiency coefficient JCi of waste heat recovery of the air compressor with an efficiency coefficient threshold:
if the efficiency coefficient JCi of the air compressor for waste heat recovery is larger than or equal to the efficiency coefficient threshold value, judging that the efficiency of the air compressor for waste heat recovery is high, generating a recovery efficiency normal signal and sending the recovery efficiency normal signal to the cloud management platform;
if the efficiency coefficient JCi of the air compressor for waste heat recovery is less than the efficiency coefficient threshold value, judging that the efficiency of the air compressor for waste heat recovery is low, marking the corresponding air compressor as an abnormal air compressor, simultaneously generating a recovery efficiency abnormal signal and sending the recovery efficiency abnormal signal and the abnormal air compressor to the cloud management platform together;
after recovery efficiency abnormal signal and unusual air compressor machine were received to the cloud management platform, generate the environment detection signal and send the environment detection signal to the environment detecting element, the environment detecting element receives the environment detection signal after, the peripheral environment information to unusual air compressor machine carries out the analysis, thereby detect unusual air compressor machine peripheral environment, unusual air compressor machine's peripheral environment information includes dust data, pressure data and humidity data, dust data is the dust content of unusual air compressor machine operation in-process peripheral environment, pressure data is the inside and outside pressure differential value of the gas holder of unusual air compressor machine, humidity data is the average humidity all day of unusual air compressor machine peripheral environment, mark unusual air compressor machine as o, o is 1, 2, … …, m, m is the positive integer, concrete analysis and detection process is as follows:
step TT 1: acquiring the dust content of the surrounding environment in the running process of the abnormal air compressor, and marking the dust content of the surrounding environment in the running process of the abnormal air compressor as FCo;
step TT 2: acquiring an internal and external pressure difference value of an air storage tank of the abnormal air compressor, and marking the internal and external pressure difference value of the air storage tank of the abnormal air compressor as YLo;
step TT 3: acquiring the average humidity of the surrounding environment of the abnormal air compressor all day, and marking the average humidity of the surrounding environment of the abnormal air compressor all day as SDo;
step TT 4: by the formula HJo ═ (FCo xs 1+ YLo xs 2+ SDo xs 3) es1+s2+s3Obtaining an environment detection coefficient HJo of the abnormal air compressor, wherein s1, s2 and s3 are proportional coefficients, s1 is more than s2 is more than s3 is more than 0, and e is a natural constant;
step TT 5: comparing the environment detection coefficient HJo of the abnormal air compressor with an environment detection coefficient threshold value:
if the environment detection coefficient HJo of the abnormal air compressor is larger than or equal to the environment detection coefficient threshold value, judging that the surrounding environment of the abnormal air compressor is abnormal, generating an environment abnormal signal and sending the environment abnormal signal to a mobile phone terminal of a maintainer;
and if the environment detection coefficient HJo of the abnormal air compressor is less than the environment detection coefficient threshold value, judging that the surrounding environment of the abnormal air compressor is normal, generating an equipment abnormal signal and sending the equipment abnormal signal to a mobile phone terminal of a maintainer.
The working principle of the invention is as follows:
a heat recycling system of an air compression station comprises a heat measuring unit, a heat detecting coefficient RLi of an air compressor is obtained through a formula, if the heat detecting coefficient RLi of the air compressor is larger than or equal to a heat detecting coefficient threshold value, the heat of the air compressor is judged to be required to be measured, after a manager receives a heat measuring signal, the heat generated by the air compressor is measured, a temperature value of the internal air before the air compressor operates is obtained and marked as Ti0, the current air temperature of the air compressor is obtained after the air compressor operates and marked as Ti1, then the constant pressure specific heat capacity of the air is obtained under the current Ti1 temperature and marked as Ci, the heat Qi released when the air compressor operates is obtained through the formula Qi Cixmxm (Ti1-Ti0), wherein m represents the air mass inside the air compressor; and then, transmitting the heat Qi released when the air compressor operates to the cloud management platform.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (3)
1. The heat recycling system of the air compression station is characterized by comprising a cloud management platform, a heat measuring unit, a recycling unit, an environment detection unit, an efficiency detection unit, a registration login unit and a database;
the heat measuring unit is used for analyzing the operation information of the air compressor, measuring the heat generated by the operation of the air compressor, wherein the operation information of the air compressor comprises temperature data, duration data and power data, the temperature data is the difference value between the temperature and the external temperature in the operation process of the air compressor, the duration data is the working duration of the continuous operation of the air compressor, the power data is the ratio of the operation power of the air compressor to the rated operation power, the air compressor is marked as i, i is 1, 2, … …, n and n is a positive integer, and the specific analysis and measurement process is as follows:
step S1: acquiring a difference value between the temperature of the air compressor in the operation process and the external temperature, and marking the difference value between the temperature of the air compressor in the operation process and the external temperature as CZi;
step S2: acquiring the continuous operation working time of the air compressor, and marking the continuous operation working time of the air compressor as SCi;
step S3: acquiring the ratio of the operating power of the air compressor to the rated operating power, and marking the ratio of the operating power of the air compressor to the rated operating power as BZi;
step S4: acquiring a heat detection coefficient RLi of the air compressor by using a formula RLi ═ beta (CZi × a1+ SCi × a2+ BZi × a3), wherein a1, a2 and a3 are proportional coefficients, a1 is greater than a2 and greater than a3 is greater than 0, and beta is an error correction factor and takes the value of 2.032125;
step S5: comparing the heat detection coefficient RLi of the air compressor with a heat detection coefficient threshold value:
if the heat detection coefficient RLi of the air compressor is larger than or equal to the heat detection coefficient threshold value, judging that the heat generated by the air compressor needs to be subjected to heat measurement, generating a heat measurement signal and sending the heat measurement signal to a mobile phone terminal of a manager;
if the heat detection coefficient RLi of the air compressor is smaller than the heat detection coefficient threshold value, judging that the heat generated by the air compressor does not need to be measured, generating a heat undetermined signal and sending the heat undetermined signal to a mobile phone terminal of a manager;
step S6: after receiving the heat measuring signal, a manager measures the heat generated by the air compressor, obtains a temperature value of the internal air before the air compressor operates, marks the temperature value as Ti0, obtains the current temperature of the internal air of the air compressor after the air compressor operates, marks the temperature value as Til, obtains the constant-pressure specific heat capacity of the air at the current Ti1 temperature, marks the constant-pressure specific heat capacity as Ci, and obtains the heat Qi released when the air compressor operates through a formula Qi, namely Ci x m x (Til-Ti0), wherein m is the air quality inside the air compressor; then, transmitting heat Qi released when the air compressor operates to a cloud management platform;
the cloud management platform generates heat recovery signals and sends the heat recovery signals to the recycling unit after receiving heat Qi released when the press operates, the recycling unit recycles the heat after receiving the heat recovery signals, and the specific recycling process is as follows:
step SS 1: acquiring the initial temperature of water in the water tank, marking the initial temperature of the water as T0, and then setting the heated water temperature by a manager according to the use mode of the water, and marking the heated water temperature as T1;
step SS 2: obtaining the specific heat capacity of the water and marking the specific heat capacity of the water as CWater (W)Obtaining the volume value of the water tank and marking the volume value of the water tank as VWater (W)Acquiring the mass of water in the water tank according to the volume value of the water tank, namely obtaining the mass of water in the water tank according to the formula mWater (W)＝α(ρvWater (W)) Wherein rho is the density of water, alpha is an error correction factor, and the value is 2.32562;
step SS 3: the heat Qi and the specific heat CWater (W)Mass m of waterWater (W)And the starting temperature T0 of water into the formula, and calculating by the heat calculation formula Qi ═ CWater (W)×mWater (W)Calculating the temperature T2 at which the heat Qi can heat the water by the aid of the heat quantity Qi (T2-T0), then comparing the temperature T2 of the water with a set water temperature T1, stopping heating the water tank if the temperature T2 of the water is larger than or equal to the set water temperature T1, generating a recovery completion signal, and sending the recovery completion signal to a cloud management platform; if the temperature T2 of the water is less than the set water temperature T1, the water tank is continuously heated;
the cloud management platform receives the recovery completion signal, generates an efficiency detection signal and sends the efficiency detection signal to the efficiency detection unit, the efficiency detection unit receives the efficiency detection signal and then analyzes the efficiency information of the air compressor, so that the heat recovery efficiency of the air compressor is detected, the efficiency information of the air compressor comprises gas production data, electric quantity data and hot water data, the gas production data is a gas production difference value before and after the air compressor performs waste heat recovery, the electric quantity data saves the number of degrees for the electric quantity of the air compressor after performing waste heat recovery, the hot water data is the ton number of hot water produced by the air compressor after performing waste heat recovery, and the specific analysis and detection process is as follows:
step T1: acquiring a gas production difference value before and after waste heat recovery of the air compressor, and marking the gas production difference value before and after waste heat recovery of the air compressor as CQi;
step T2: acquiring the electric quantity saving degree of the air compressor after waste heat recovery, and marking the electric quantity saving degree of the air compressor after waste heat recovery as DSi;
step T3: acquiring the tonnage of hot water produced after waste heat recovery of an air compressor, and marking the tonnage of hot water produced after waste heat recovery of the air compressor as RSi;
step T4: by the formula
Obtaining an efficiency coefficient JCi of waste heat recovery of the air compressor, wherein b1, b2 and b3 are proportional coefficients, and b1 is more than b2 is more than b3 is more than 0;
step T5: comparing an efficiency coefficient JCi of waste heat recovery of the air compressor with an efficiency coefficient threshold:
if the efficiency coefficient JCi of the air compressor for waste heat recovery is larger than or equal to the efficiency coefficient threshold value, judging that the efficiency of the air compressor for waste heat recovery is high, generating a recovery efficiency normal signal and sending the recovery efficiency normal signal to the cloud management platform;
if the efficiency coefficient JCi of the air compressor for waste heat recovery is less than the efficiency coefficient threshold value, judging that the efficiency of the air compressor for waste heat recovery is low, marking the corresponding air compressor as an abnormal air compressor, simultaneously generating a recovery efficiency abnormal signal and sending the recovery efficiency abnormal signal and the abnormal air compressor to the cloud management platform together;
the method comprises the steps that after a recovery efficiency abnormal signal and an abnormal air compressor are received by a cloud management platform, an environment detection signal is generated and sent to an environment detection unit, after the environment detection unit receives the environment detection signal, the surrounding environment information of the abnormal air compressor is analyzed, so that the surrounding environment of the abnormal air compressor is detected, the surrounding environment information of the abnormal air compressor comprises dust data, pressure data and humidity data, the dust data is the dust content of the surrounding environment in the operation process of the abnormal air compressor, the pressure data is the difference value of the internal and external pressures of an air storage tank of the abnormal air compressor, the humidity data is the average humidity of the surrounding environment of the abnormal air compressor all day, the abnormal air compressor is marked as o, o is 1, 2, … …, m and m is a positive integer;
the registration login unit is used for the manager and the maintainer to submit the information of the manager and the information of the maintainer through the mobile phone terminal, and the manager and the maintainer which are successfully registered are sent to the database to be stored.
2. The heat recycling system of the air compressor station as claimed in claim 1, wherein the specific analysis and detection process of the ambient environment of the abnormal air compressor is as follows:
step TT 1: acquiring the dust content of the surrounding environment in the running process of the abnormal air compressor, and marking the dust content of the surrounding environment in the running process of the abnormal air compressor as FCo;
step TT 2: acquiring an internal and external pressure difference value of an air storage tank of the abnormal air compressor, and marking the internal and external pressure difference value of the air storage tank of the abnormal air compressor as YLo;
step TT 3: acquiring the average humidity of the surrounding environment of the abnormal air compressor all day, and marking the average humidity of the surrounding environment of the abnormal air compressor all day as SDo;
step TT 4: by the formula HJo ═ (FCo xs 1+ YLo xs 2+ SDo xs 3) es1+s2+s3Obtaining an environment detection coefficient HJo of the abnormal air compressor, wherein s1, s2 and s3 are proportional coefficients, s1 is more than s2 is more than s3 is more than 0, and e is a natural constant;
step TT 5: comparing the environment detection coefficient HJo of the abnormal air compressor with an environment detection coefficient threshold value:
if the environment detection coefficient HJo of the abnormal air compressor is larger than or equal to the environment detection coefficient threshold value, judging that the surrounding environment of the abnormal air compressor is abnormal, generating an environment abnormal signal and sending the environment abnormal signal to a mobile phone terminal of a maintainer;
and if the environment detection coefficient HJo of the abnormal air compressor is less than the environment detection coefficient threshold value, judging that the surrounding environment of the abnormal air compressor is normal, generating an equipment abnormal signal and sending the equipment abnormal signal to a mobile phone terminal of a maintainer.
3. The air compression station heat recycling system according to claim 1, wherein the manager information includes a name, an age, an attendance time, and a mobile phone number for personal real name authentication of the manager, and the maintainer information includes a name, an age, an attendance time, and a mobile phone number for personal real name authentication of the maintainer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110695842.3A CN113449977B (en) | 2021-06-23 | 2021-06-23 | Heat recycling system of air compression station |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110695842.3A CN113449977B (en) | 2021-06-23 | 2021-06-23 | Heat recycling system of air compression station |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113449977A CN113449977A (en) | 2021-09-28 |
| CN113449977B true CN113449977B (en) | 2022-02-22 |
Family
ID=77812314
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110695842.3A Active CN113449977B (en) | 2021-06-23 | 2021-06-23 | Heat recycling system of air compression station |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113449977B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107191992A (en) * | 2017-05-26 | 2017-09-22 | 西安纺织集团有限责任公司 | A kind of air compression station heat recovery cyclic utilization system |
| CN208252306U (en) * | 2018-05-31 | 2018-12-18 | 山东安悦节能技术有限公司 | The recycling of automobile industry residual heat of air compressor and chilled water storage system |
| CN112571149A (en) * | 2020-12-05 | 2021-03-30 | 董云春 | Cooling, heat dissipation monitoring and alarming system of large numerical control machine tool |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9115603B2 (en) * | 2012-07-24 | 2015-08-25 | Electratherm, Inc. | Multiple organic Rankine cycle system and method |
| JP5985405B2 (en) * | 2013-01-28 | 2016-09-06 | 株式会社日立産機システム | Waste heat recovery system for oil-cooled gas compressor |
-
2021
- 2021-06-23 CN CN202110695842.3A patent/CN113449977B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107191992A (en) * | 2017-05-26 | 2017-09-22 | 西安纺织集团有限责任公司 | A kind of air compression station heat recovery cyclic utilization system |
| CN208252306U (en) * | 2018-05-31 | 2018-12-18 | 山东安悦节能技术有限公司 | The recycling of automobile industry residual heat of air compressor and chilled water storage system |
| CN112571149A (en) * | 2020-12-05 | 2021-03-30 | 董云春 | Cooling, heat dissipation monitoring and alarming system of large numerical control machine tool |
Non-Patent Citations (2)
| Title |
|---|
| 有油螺杆空压机余热回收的换热器选型及应用技术的研究;程艳;《中国优秀硕士学位论文全文数据库 工程科技I辑》;20160930(第09期);全文 * |
| 王近邻;空压站余热回收系统节能设计;《中国建筑金属结构》;20130430(第5期);第126-128页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113449977A (en) | 2021-09-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114665597A (en) | Intelligent power supply system | |
| CN116632983A (en) | Charging and discharging control system suitable for outdoor energy storage power supply | |
| CN114801751A (en) | Automobile battery fault prediction system based on data analysis | |
| CN113449977B (en) | Heat recycling system of air compression station | |
| CN115389958A (en) | Lithium ion battery operation safety evaluation method and system | |
| CN114422405A (en) | Safety detection system and method for payment environment | |
| CN115473924A (en) | Carbon emission metering system based on thing networking block chain | |
| CN104330117A (en) | Transformer substation switch cabinet temperature and humidity measurement system | |
| CN111682925A (en) | Data acquisition and processing method for intelligent street lamp | |
| CN113611096A (en) | Electric energy consumption monitoring and early warning system for air compression station | |
| CN114065955A (en) | Power cable visual monitoring maintenance management system based on GIS | |
| CN105844901A (en) | Security energy efficiency monitoring terminal based on tamper-proof technology and monitoring method of security energy efficiency monitoring terminal | |
| CN112488521A (en) | Asset management and control implementation method of energy consumption platform | |
| CN117474565A (en) | Carbon accounting digital twin energy management system | |
| CN103105411A (en) | Self-calibration sterilizing gas concentration detection equipment based on wireless data transmission technology | |
| CN115208032B (en) | Charging safety detection method for super capacitor | |
| CN115860583A (en) | Landfill biogas collection and evaluation method, system and medium based on big data | |
| CN113919239B (en) | Intelligent internal threat detection method and system based on space-time feature fusion | |
| CN116015209A (en) | Photovoltaic power station component performance management method, system, device and storage medium | |
| CN214067331U (en) | Sf6 density relay checking device with image recognition function | |
| CN110556595B (en) | Method for predicting quality unbalance of lithium iron phosphate battery safety management system for energy storage | |
| CN110888100A (en) | Single-phase intelligent electric energy meter online on-load detection system and method | |
| CN115983835B (en) | Wireless heating energy consumption analysis and supervision system based on Internet of things | |
| CN117406090B (en) | Lithium ion battery power consumption detection method and device | |
| CN112491038B (en) | Probability distribution estimation method and system for service life of power distribution network equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A Heat Recovery and Utilization System for Air Compression Station Effective date of registration: 20231020 Granted publication date: 20220222 Pledgee: Guangdong Hengfu Financial Leasing Co.,Ltd. Pledgor: Guangdong xinzuan Energy Saving Technology Co.,Ltd. Registration number: Y2023980062019 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right |