CN111811108A - Heat exchanger filth blockage detection method and device - Google Patents
Heat exchanger filth blockage detection method and device Download PDFInfo
- Publication number
- CN111811108A CN111811108A CN202010512245.8A CN202010512245A CN111811108A CN 111811108 A CN111811108 A CN 111811108A CN 202010512245 A CN202010512245 A CN 202010512245A CN 111811108 A CN111811108 A CN 111811108A
- Authority
- CN
- China
- Prior art keywords
- heat exchanger
- data
- state data
- actual
- dirty
- 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.)
- Granted
Links
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/32—Responding to malfunctions or emergencies
- F24F11/39—Monitoring filter performance
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Human Computer Interaction (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention relates to a heat exchanger filth blockage detection method and a device, which comprises the steps of collecting actual operation data of a heat exchanger during operation, and calculating to obtain theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked; acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates; and determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data. The method can judge the filth blockage degree of the heat exchanger of the unit based on historical data, improves the judging effect and the detection speed, solves the problems of overlarge algorithm error and insufficient stability caused by few monitored operating parameters, improves the accuracy rate of the filth blockage judgment of the heat exchanger, and can summarize the development trend through the historical operating data and the real-time operating data so as to accurately predict the filth blockage condition of the heat exchanger in the future.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a heat exchanger filth blockage detection method and device.
Background
The air conditioner can make the pipeline in the unit heat exchanger take place filth under the influence of factors such as long-time use, quality of water of intaking very easily and stifled to influence the heat transfer effect of unit, lead to the parameter of air conditioner unusual (like the host computer electric current increase), the energy efficiency ratio reduces, thereby influence the operation of unit and customer's use experience, then it is very necessary to control, detect and the analysis of the filth stifled degree of air conditioner heat exchanger.
In the related technology, the method for detecting the filth blockage degree of the air conditioner heat exchange device is mainly based on single or a small amount of operation parameters of the air conditioner in the current operation state, real-time parameter acquisition is carried out through a series of parameter acquisition devices, and the filth blockage degree is given through parameter calculation and logic inference; or the filth blockage degree of the heat exchange device is calculated and deduced based on the rotating speed of the fan of the air conditioner and the corresponding power variable quantity. However, the method has low efficiency when being used for detecting and analyzing the heat exchanger, and the following problems can be caused when the filth blockage degree of the heat exchanger is detected and analyzed:
1) the deployment difficulty is high; the method for detecting the filth blockage degree of the heat exchanger of the unit needs to acquire a large amount of first operation data of the unit in real time and perform a large amount of calculation in an air conditioner system, has high requirements on the real-time performance of the data, and has high requirements on the real-time transmission capacity of network signals and data at the location of the unit and the calculation capacity of the unit, so that the method is difficult to deploy and land and has low detection speed.
2) The method error is large; the overall filth blockage degree of the heat exchanger is judged only based on a small amount of operation parameters such as fan pressure difference or fan power difference, and the influence of other non-filth blockage reasons on the operation parameters is not considered, so that the algorithm judgment error is large.
3) The function is not perfect; only the function of monitoring and judging the filth blockage degree of the air-conditioning heat exchanger is realized, and the advance prediction and early warning cannot be realized, so that corresponding maintenance measures cannot be taken in time.
Disclosure of Invention
In view of the above, the present invention provides a method and a device for detecting filth blockage of a heat exchanger, so as to solve the problem of low efficiency in detecting and analyzing the heat exchanger in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme: a heat exchanger filth blockage detection method comprises the following steps:
acquiring actual operation data of the heat exchanger during operation, and calculating to obtain theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked;
acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates;
and determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data.
Further, acquiring operation data and operation state data when the heat exchanger is not dirty and blocked;
and performing multiple regression analysis on the operation data and the operation state data to determine the operation state model.
Further, the determining whether the heat exchanger is dirty or not according to the actual operation state data and the theoretical operation state data includes:
calculating the absolute value of the difference value between the actual running state data and the theoretical running state data;
and if the absolute value is larger than a preset data threshold value, determining that the heat exchanger is dirty and blocked.
Further, the determining whether the heat exchanger is dirty or blocked according to the actual operating state data and the theoretical operating state data includes:
calculating an absolute value of a difference between the first actual operating state data and the first theoretical operating state data, and calculating an absolute value of a difference between the second actual operating state data and the second theoretical operating state data;
and if the two absolute values are both larger than a preset data threshold value, and the time difference value between the first time and the second time is larger than a preset time threshold value, determining that the heat exchanger is dirty and blocked.
Further, the data threshold includes a plurality of data thresholds, and the determining that the heat exchanger is dirty includes:
and comparing the absolute value with the plurality of data thresholds to determine the level of the dirty blockage of the heat exchanger.
Further, when the heat exchanger is determined to be dirty and blocked, a dirty and blocked prediction model is established or updated according to the occurrence time, the actual operation data and the actual operation state data of the heat exchanger when dirty and blocked occur.
Further, the method also comprises the following steps:
and predicting the prediction time and/or the prediction operation state data of the heat exchanger about to generate filth blockage according to the filth blockage prediction model, and/or predicting the filth blockage level according to the prediction operation state data.
Further, the operational data includes at least one of:
the inlet water temperature of the chilled water, the outlet water temperature of the chilled water, the inlet water temperature of the cooling water, the outlet water temperature of the cooling water, the condensation temperature and the evaporation temperature; and/or the presence of a gas in the gas,
the operational status data comprises at least one of:
end temperature difference value, load value.
Further, the heat exchanger is an air conditioner heat exchanger.
The embodiment of the application provides a dirty stifled degree detection device of heat exchanger, includes:
the calculation module is used for acquiring actual operation data of the heat exchanger during operation and calculating theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked;
the acquisition module is used for acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates;
and the determining module is used for determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data.
By adopting the technical scheme, the invention can achieve the following beneficial effects:
1) and the deployment difficulty is small. According to the method and the device, the filth blockage degree of the heat exchanger is judged only based on the parameters returned by the sensor arranged in the air conditioner, and the structure or the system of the air conditioner does not need to be changed; and a large amount of calculation and algorithm training are only required to be deployed and finished at the end of the server when the air conditioner uses the scheme for the first time, the algorithm time complexity is low in the subsequent real-time monitoring and analyzing and judging stage, the configuration requirement on the server is low, the analyzing and judging speed is high, the dirty and blocked degree of the heat exchanger of the unit can be judged based on historical data, the poor judging effect caused by the poor network signal or data transmission capacity of a method for judging based on real-time data is avoided, the deployment difficulty of the analysis method can be reduced, and the detection and prediction speed is improved.
2) The algorithm error is small. Because what this application provided is based on a plurality of little operating parameters of correlation come to carry out the comprehensive analysis to the filth stifled degree of air conditioner heat exchanger, solved because of the operating parameter of monitoring leads to the problem that the algorithm error is too big and stability is not enough less, reduced the heat exchanger filth and blocked up the error of judging.
3) And realizing a prediction function. The development trend can be summarized by combining the historical first operation data and the real-time first operation data, so that the future heat exchanger filth blockage situation can be accurately predicted, and the problems of hardware loss, refrigeration efficiency reduction and the like of the air conditioner heat exchanger caused by heat exchanger filth blockage can be avoided by adopting corresponding control measures in advance.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the steps of the method for detecting fouling of a heat exchanger according to the present invention;
FIG. 2 is a schematic diagram illustrating the steps of determining an operating condition model according to the present invention;
FIG. 3 is a schematic flow chart of a heat exchanger filth blockage detection method according to the present invention;
FIG. 4 is another schematic flow chart of the method for detecting fouling of a heat exchanger according to the present invention;
fig. 5 is a schematic structural diagram of the heat exchanger filth blockage detection device of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
A specific method for detecting the degree of fouling of a heat exchanger provided in the embodiments of the present application is described below with reference to the accompanying drawings.
As shown in fig. 1, a method for detecting a degree of fouling of a heat exchanger provided in an embodiment of the present application includes:
s101, acquiring actual operation data of the heat exchanger during operation, and calculating to obtain theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked;
the operation data is acquired by using a sensor when the heat exchanger operates, the operation data comprises operation data of various operation parameters, and the operation parameters can also be load and/or end temperature difference calculated by various operation parameters, such as: the operation parameters comprise chilled water inlet temperature, chilled water outlet temperature, cooling water inlet temperature, cooling water outlet temperature, condensation temperature and evaporation temperature which are acquired by a temperature sensor, wherein the end temperature difference is the cooling water outlet temperature-condensation temperature. It should be noted that the operation state model is a multiple regression equation, and the sensors acquire the operation data of the operation parameters and upload the operation data to the server for storage.
It can be understood that the operation state model is determined according to the operation data and the operation state data when the heat exchanger is free from the filth blockage, and is a theoretical operation state when the heat exchanger is free from the filth blockage. The running data of the air-conditioning heat exchanger without filth blockage is used for analysis, and the interference of the running data of the heat exchanger with filth blockage on the initial model is eliminated.
S102, acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates;
the sensor is adopted to collect the actual operation data of the heat exchanger during real-time operation, the actual operation data is substituted into the operation state model, and the fitting value of the actual operation state, namely the actual operation state data, can be obtained through calculation.
S103, determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data.
And when the heat exchanger is not dirty and blocked, the operation data is substituted into the operation state model to obtain theoretical operation state data, the actual operation state data is substituted into the operation state model to obtain actual operation state data, the actual operation state data is compared with the theoretical operation state data, and whether the heat exchanger is dirty and blocked is judged according to a comparison result.
Preferably, the heat exchanger is an air conditioner heat exchanger.
The working principle of the heat exchanger filth blockage degree detection method is as follows: the method comprises the steps of collecting and analyzing running data of a unit under the condition that a heat exchanger is not dirty and blocked by adopting a regression analysis method to obtain a fitting equation when the heat exchanger is not dirty and blocked, substituting the collected actual running data into actual running state data obtained by the equation, and judging whether the unit is dirty and blocked or not according to the actual running state data and theoretical state data.
In some embodiments, as shown in fig. 2, the method for detecting the degree of fouling of a heat exchanger provided by the present application further includes:
s201, acquiring running data and running state data of the heat exchanger without dirt blockage;
s202, performing multiple regression analysis on the operation data and the operation state data to determine the operation state model.
Specifically, the operating state model is a multiple regression equation in the form of y ═ kx1+kx2+…kxn+ b, wherein x is an operation parameter, namely, the operation parameter is a plurality of the inlet water temperature of the chilled water, the outlet water temperature of the chilled water, the inlet water temperature of the cooling water, the outlet water temperature of the cooling water, the condensation temperature, the evaporation temperature, the end temperature difference or the current, the operation parameter can also comprise the current, and the load is calculated through the current; and selecting the operation data of a plurality of operation parameters when the heat exchanger is not dirty and blocked to perform multiple linear regression analysis to obtain an optimal multiple regression equation, namely an operation state model.
In some embodiments, the determining whether the heat exchanger is dirty or not according to the actual operating state data and the theoretical operating state data includes:
calculating the absolute value of the difference value between the actual running state data and the theoretical running state data;
and if the absolute value is larger than a preset data threshold value, determining that the heat exchanger is dirty and blocked.
Specifically, the acquired actual operation data is substituted into the equation to obtain actual operation state data, the actual operation state data is subtracted from the theoretical operation state data, an absolute value is obtained from the difference value, the absolute value is compared with a preset data threshold value, and if the absolute value is larger than the data threshold value, the situation that the heat exchanger is jammed is indicated.
In some embodiments, the determining whether the heat exchanger is dirty or not according to the actual operating state data and the theoretical operating state data includes:
calculating an absolute value of a difference between the first actual operating state data and the first theoretical operating state data, and calculating an absolute value of a difference between the second actual operating state data and the second theoretical operating state data;
and if the two absolute values are both larger than a preset data threshold value, and the time difference value between the first time and the second time is larger than a preset time threshold value, determining that the heat exchanger is dirty and blocked.
Preferably, the data threshold includes a plurality of data thresholds, and the determining that the heat exchanger is dirty includes:
and comparing the absolute value with the plurality of data thresholds to determine the level of the dirty blockage of the heat exchanger.
Specifically, as shown in fig. 3, for example, an actual end temperature difference value and a theoretical end temperature difference value are obtained and compared; presetting a data threshold D and a time threshold T; substituting the daily operation data of the operation parameters of the air conditioner into the operation state model one by one, and calculating an end temperature difference value Y, namely a fitting value when filth blockage does not occur; acquiring daily operation data of a subsequent heat exchanger, obtaining the current end temperature difference through the operation data, substituting the current end temperature difference into an operation state equation, and calculating to obtain an end temperature difference value Y of the current timeTd(ii) a And the temperature difference value Y between the Y and the end temperature of the heat exchanger at the current timeTdComparing, when the absolute value of the difference value is higher than the dataAnd when the threshold value D is reached, judging that the heat exchanger of the unit is in a dirty and blocked state.
After the heat exchanger is determined to be in the dirty blocking state, when the duration time of the unit in the dirty blocking state is longer than a preset time threshold T, a unit dirty blocking alarm is sent to a unit receiving device, an operation and maintenance department and a client through a server and network equipment, and dirty blocking solutions are provided, wherein the dirty blocking solutions include but are not limited to cleaning of a heat exchanger shell and tube, adjustment of a unit control strategy, an operation mode and the like.
Level thresholds of different levels may be preset, the absolute value compared to the level threshold, and the level of visceral congestion determined by comparison, for example: the level threshold is (M, N); when the absolute value is less than M, the light level is judged, when the absolute value is between M and N, the medium level is judged, and when the absolute value is more than N, the heavy level is judged.
Preferably, the method further comprises the following steps:
and when the heat exchanger is determined to be dirty and blocked, establishing or updating a dirty and blocked prediction model according to the occurrence time, the actual operation data and the actual operation state data of the dirty and blocked occurrence.
Preferably, the prediction time and/or the prediction operation state data of the heat exchanger about to generate the filth blockage are predicted according to the filth blockage prediction model, and/or the filth blockage grade is predicted according to the prediction operation state data.
As shown in FIG. 4, assume that the heat exchanger is at tmDirty blockage is detected at any moment, and the corresponding operation data is xmAnd obtaining the end temperature difference value (x) through a daily operation state model when the heat exchanger is not dirty and blocked1，x2，x3…xm-1) And the end temperature difference value (x) after the filth blockage alarm occursm，xm+1，…xn) Put together with time (t)1，t2…tn) And performing time series analysis on the server, and calculating an optimal regression equation between the time and the comprehensive value of the filth blockage degree, namely a filth blockage prediction model, wherein the model is updated in real time along with the operation data.
The future time (t) is obtained by the equationn+1，tn+2…) end temperature difference value (Z)n+1，Zn+2…) and by setting a threshold value (P, Q) for the tip temperature difference, when the tip temperature difference Z isi<P, it can be determined that the unit will be at that time tk+1The temperature difference value P of the machine set end is in a mild filth blockage degree<Zi<Q, it can be determined that the heat exchanger will be at that time ti+1At the medium degree of visceral obstruction, when the end temperature difference value Zi>When Q, it can be determined that the unit will be at that time ti+1The system is in a severe filth blockage degree, a prediction result is stored in a result set, a heat exchanger filth blockage prediction report is generated at regular intervals based on the result set and is transmitted to a unit receiving device, an operation and maintenance department and a client through a server and network equipment, so that a corresponding air conditioner control strategy and a corresponding maintenance measure are prepared in advance, and the damage caused by filth blockage of an air conditioner heat exchanger is prevented in advance.
Preferably, the operational data comprises at least one of:
the inlet water temperature of the chilled water, the outlet water temperature of the chilled water, the inlet water temperature of the cooling water, the outlet water temperature of the cooling water, the condensation temperature and the evaporation temperature; and/or the presence of a gas in the gas,
the operational status data comprises at least one of:
end temperature difference value, load value.
The method comprises the following steps that a temperature sensor is used for collecting chilled water inlet temperature, chilled water outlet temperature, cooling water inlet temperature, cooling water outlet temperature, condensation temperature and evaporation temperature, a current sensor is used for collecting current, load is obtained by collecting host current through the current sensor and calculating, it needs to be explained that the current calculation method for calculating the load adopts the prior art, the description is omitted here, and the end temperature difference is cooling water outlet temperature-condensation temperature; and substituting the end temperature difference and the load into the running state model respectively to calculate to obtain a corresponding end temperature difference value and a corresponding load value.
Preferably, the heat exchanger is an air conditioner heat exchanger.
In some embodiments, as shown in fig. 5, an embodiment of the present application provides a method, including:
the calculation module 501 is configured to acquire actual operation data of the heat exchanger during operation, and calculate theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked;
an obtaining module 502, configured to obtain actual operation state data corresponding to the actual operation data when the heat exchanger operates;
a determining module 503, configured to determine whether the heat exchanger is dirty or not according to the actual operating state data and the theoretical operating state data.
The working principle of the heat exchanger filth blockage degree detection device provided by the application is that a calculation module 501 collects actual operation data of the heat exchanger during operation and calculates theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked; an obtaining module 502 obtains actual operation state data corresponding to the actual operation data when the heat exchanger operates; the determining module 503 determines whether the heat exchanger is dirty or not according to the actual operating state data and the theoretical operating state data.
The embodiment of the application provides computer equipment, which comprises a processor and a memory connected with the processor;
the memory is used for storing a computer program, and the computer program is used for executing the heat exchanger filth degree detection method provided by any one of the above embodiments;
the processor is used to call and execute the computer program in the memory.
In summary, the present invention provides a method and an apparatus for detecting a degree of filth blockage of a heat exchanger, including acquiring actual operation data of the heat exchanger during operation, and calculating to obtain theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked; acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates; and determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data. The technical scheme of the air conditioner has small deployment difficulty, and the dirty and blocked degree of the heat exchanger is judged based on the parameters returned by the sensor arranged in the air conditioner without changing the structure or the system of the air conditioner; and a large amount of calculation and algorithm training are only required to be completed by deploying at the server end when the air conditioner uses the scheme for the first time, the algorithm time complexity is low in the subsequent real-time monitoring and analyzing and judging stage, the configuration requirement on the server is low, and the analyzing and judging speed is high. And the dirty and blocked degree of the heat exchanger of the unit can be judged based on historical data, so that the poor judgment effect caused by poor network signal or data transmission capacity of a real-time data-based judging method is avoided, the deployment difficulty of the analysis method can be reduced, and the detection and prediction speed is improved. Secondly, the algorithm error is small, comprehensive analysis is carried out on the filth blockage degree of the air-conditioning heat exchanger based on a plurality of operation parameters with small correlation, the problems of overlarge algorithm error and insufficient stability caused by few monitored operation parameters are solved, and the heat exchanger filth blockage judgment error is reduced. In addition, the method and the device can realize a prediction function, and can combine historical operation data and real-time operation data to summarize the development trend so as to accurately predict the filth blockage condition of the heat exchanger in the future, so that corresponding control measures can be taken in advance to avoid the problems of hardware loss, refrigeration efficiency reduction and the like of the air-conditioning heat exchanger caused by filth blockage of the heat exchanger.
It is to be understood that the embodiments of the method provided above correspond to the embodiments of the apparatus described above, and the corresponding specific contents may be referred to each other, which is not described herein again.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for detecting the filth blockage degree of a heat exchanger is characterized by comprising the following steps:
acquiring actual operation data of the heat exchanger during operation, and calculating to obtain theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked;
acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates;
and determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data.
2. The method of claim 1, further comprising:
acquiring operation data and operation state data when the heat exchanger is not dirty and blocked;
and performing multiple regression analysis on the operation data and the operation state data to determine the operation state model.
3. The method of claim 1, wherein said determining whether the heat exchanger is fouled based on the actual operating condition data and the theoretical operating condition data comprises:
calculating the absolute value of the difference value between the actual running state data and the theoretical running state data;
and if the absolute value is larger than a preset data threshold value, determining that the heat exchanger is dirty and blocked.
4. The method of claim 1, wherein the actual operating state data comprises first actual operating state data corresponding to a first time and second actual operating state data corresponding to a second time, the theoretical operating state data comprises first theoretical operating state data and second theoretical operating state data corresponding to the first actual operating state data and the second actual operating state data, respectively, and the determining whether the heat exchanger is dirty or not according to the actual operating state data and the theoretical operating state data comprises:
calculating an absolute value of a difference between the first actual operating state data and the first theoretical operating state data, and calculating an absolute value of a difference between the second actual operating state data and the second theoretical operating state data;
and if the two absolute values are both larger than a preset data threshold value, and the time difference value between the first time and the second time is larger than a preset time threshold value, determining that the heat exchanger is dirty and blocked.
5. The method of claim 3 or 4, wherein the data threshold comprises a plurality of data thresholds, and wherein the determining that the heat exchanger is fouled comprises:
and comparing the absolute value with the plurality of data thresholds to determine the level of the dirty blockage of the heat exchanger.
6. The method of claim 1, further comprising:
and when the heat exchanger is determined to be dirty and blocked, establishing or updating a dirty and blocked prediction model according to the occurrence time, the actual operation data and the actual operation state data of the dirty and blocked occurrence.
7. The method of claim 6, further comprising:
and predicting the prediction time and/or the prediction operation state data of the heat exchanger about to generate filth blockage according to the filth blockage prediction model, and/or predicting the filth blockage level according to the prediction operation state data.
8. The method according to any one of claims 1 to 4 and 6 to 7,
the operational data includes at least one of:
the inlet water temperature of the chilled water, the outlet water temperature of the chilled water, the inlet water temperature of the cooling water, the outlet water temperature of the cooling water, the condensation temperature and the evaporation temperature; and/or the presence of a gas in the gas,
the operational status data comprises at least one of:
end temperature difference value, load value.
9. The method of any one of claims 1-4, 6-7, wherein the heat exchanger is an air conditioner heat exchanger.
10. A heat exchanger filth blockage degree detection device is characterized by comprising:
the calculation module is used for acquiring actual operation data of the heat exchanger during operation and calculating theoretical operation state data according to the actual operation data and a predetermined operation state model; the operation state model is determined according to operation data and operation state data when the heat exchanger is not dirty and blocked;
the acquisition module is used for acquiring actual operation state data corresponding to the actual operation data when the heat exchanger operates;
and the determining module is used for determining whether the heat exchanger is dirty or not according to the actual running state data and the theoretical running state data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010512245.8A CN111811108B (en) | 2020-06-08 | 2020-06-08 | Heat exchanger filth blockage detection method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010512245.8A CN111811108B (en) | 2020-06-08 | 2020-06-08 | Heat exchanger filth blockage detection method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111811108A true CN111811108A (en) | 2020-10-23 |
| CN111811108B CN111811108B (en) | 2021-07-09 |
Family
ID=72845884
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010512245.8A Active CN111811108B (en) | 2020-06-08 | 2020-06-08 | Heat exchanger filth blockage detection method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111811108B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112484232A (en) * | 2020-11-23 | 2021-03-12 | 珠海格力电器股份有限公司 | Air conditioner control method and device with expert diagnosis function and air conditioning unit |
| CN112781175A (en) * | 2021-01-04 | 2021-05-11 | 广东美的暖通设备有限公司 | Heat exchanger filth blockage detection method and device, air conditioning equipment and storage medium |
| CN112944582A (en) * | 2021-03-01 | 2021-06-11 | 青岛海尔（胶州）空调器有限公司 | Method and device for prompting self-cleaning of air conditioner and air conditioner |
| CN113531845A (en) * | 2021-07-09 | 2021-10-22 | 青岛海尔空调器有限总公司 | Method for controlling self-cleaning in indoor heat exchanger |
| CN114235451A (en) * | 2021-11-15 | 2022-03-25 | 青岛海尔空调电子有限公司 | Heat exchanger detection method, storage medium and electronic device |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104949276A (en) * | 2015-06-24 | 2015-09-30 | 海信（山东）空调有限公司 | Air conditioner running state self-detecting method and system |
| CN109959117A (en) * | 2019-03-22 | 2019-07-02 | 四川长虹空调有限公司 | A kind of dirty stifled detection method of air-conditioning internal machine, device, air conditioner and storage medium |
| CN110553377A (en) * | 2019-10-08 | 2019-12-10 | 芜湖美智空调设备有限公司 | filth blockage detection method and system for outdoor heat exchanger of air conditioner and air conditioner |
| CN110986285A (en) * | 2019-10-31 | 2020-04-10 | 青岛海尔空调器有限总公司 | Self-cleaning control method for heat exchanger of indoor unit of air conditioner and air conditioner |
| CN111140990A (en) * | 2019-12-23 | 2020-05-12 | 珠海格力电器股份有限公司 | Filth blockage detection method for air conditioner heat exchanger and air conditioner |
| WO2020095521A1 (en) * | 2018-11-09 | 2020-05-14 | 株式会社 東芝 | Air-conditioning control device, refrigerant circuit control device, inspection method, and program |
| CN111288607A (en) * | 2020-03-04 | 2020-06-16 | 宁波奥克斯电气股份有限公司 | Method and device for detecting filth blockage of air conditioner heat exchanger and air conditioner |
-
2020
- 2020-06-08 CN CN202010512245.8A patent/CN111811108B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104949276A (en) * | 2015-06-24 | 2015-09-30 | 海信（山东）空调有限公司 | Air conditioner running state self-detecting method and system |
| WO2020095521A1 (en) * | 2018-11-09 | 2020-05-14 | 株式会社 東芝 | Air-conditioning control device, refrigerant circuit control device, inspection method, and program |
| CN109959117A (en) * | 2019-03-22 | 2019-07-02 | 四川长虹空调有限公司 | A kind of dirty stifled detection method of air-conditioning internal machine, device, air conditioner and storage medium |
| CN110553377A (en) * | 2019-10-08 | 2019-12-10 | 芜湖美智空调设备有限公司 | filth blockage detection method and system for outdoor heat exchanger of air conditioner and air conditioner |
| CN110986285A (en) * | 2019-10-31 | 2020-04-10 | 青岛海尔空调器有限总公司 | Self-cleaning control method for heat exchanger of indoor unit of air conditioner and air conditioner |
| CN111140990A (en) * | 2019-12-23 | 2020-05-12 | 珠海格力电器股份有限公司 | Filth blockage detection method for air conditioner heat exchanger and air conditioner |
| CN111288607A (en) * | 2020-03-04 | 2020-06-16 | 宁波奥克斯电气股份有限公司 | Method and device for detecting filth blockage of air conditioner heat exchanger and air conditioner |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112484232A (en) * | 2020-11-23 | 2021-03-12 | 珠海格力电器股份有限公司 | Air conditioner control method and device with expert diagnosis function and air conditioning unit |
| CN112484232B (en) * | 2020-11-23 | 2022-10-14 | 珠海格力电器股份有限公司 | Air conditioner control method and device with expert diagnosis function and air conditioning unit |
| CN112781175A (en) * | 2021-01-04 | 2021-05-11 | 广东美的暖通设备有限公司 | Heat exchanger filth blockage detection method and device, air conditioning equipment and storage medium |
| CN112944582A (en) * | 2021-03-01 | 2021-06-11 | 青岛海尔（胶州）空调器有限公司 | Method and device for prompting self-cleaning of air conditioner and air conditioner |
| WO2022183769A1 (en) * | 2021-03-01 | 2022-09-09 | 青岛海尔空调器有限总公司 | Method and device for prompting self-cleaning of air conditioner and air conditioner |
| CN113531845A (en) * | 2021-07-09 | 2021-10-22 | 青岛海尔空调器有限总公司 | Method for controlling self-cleaning in indoor heat exchanger |
| CN114235451A (en) * | 2021-11-15 | 2022-03-25 | 青岛海尔空调电子有限公司 | Heat exchanger detection method, storage medium and electronic device |
| CN114235451B (en) * | 2021-11-15 | 2023-09-26 | 青岛海尔空调电子有限公司 | Heat exchanger detection method, storage medium and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111811108B (en) | 2021-07-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111811108B (en) | Heat exchanger filth blockage detection method and device | |
| US7536371B2 (en) | Apparatus and method for the analysis of a process having parameter-based faults | |
| CN111401582B (en) | Abnormity identification method and monitoring platform for domestic sewage treatment facility | |
| KR101573296B1 (en) | Prediction method of abnormal data, and a computer-readable storege medium having program to perform the same | |
| JP4017272B2 (en) | Plant state estimation / prediction apparatus and method | |
| CN113033015B (en) | Degradation equipment residual life prediction method considering two-stage self-adaptive Wiener process | |
| CN109040277A (en) | A kind of long-distance monitoring method and device of server | |
| CN117082105B (en) | Environment-friendly intelligent hospital facility monitoring system and method | |
| US10642247B2 (en) | Cell control system | |
| CN117308498A (en) | Cloud storage-based intelligent monitoring and management method and system for temperature of refrigeration house | |
| CN104930340B (en) | Distributed wireless monitoring device and system for steam heat-supply network steam trap as well as working method | |
| JP6369895B2 (en) | Motor abnormality detection system, motor abnormality detection method, and motor abnormality detection program | |
| CN116225102B (en) | Mobile energy storage communication temperature rise automatic monitoring system and device | |
| CN117252383A (en) | Flood discharge gate running state monitoring method, system, electronic equipment and storage medium | |
| JP2016177676A (en) | Diagnosis device, diagnosis method, diagnosis system and diagnosis program | |
| CN117091273A (en) | Control method and device for self-adaptive learning data model of central air conditioning system | |
| CN109209781B (en) | The Fault Locating Method and device of wind power generating set | |
| CN113297194B (en) | Method for identifying and cleaning false data of spare capacity of electric automobile aggregator | |
| KR20160038000A (en) | Method of monitoring and operating heat exchangers for fuels containing carbon | |
| JP6126316B2 (en) | Maintenance support system and maintenance support method | |
| CN105469564A (en) | Vibration data wireless collection and transmission apparatus | |
| CN117369604B (en) | Flow control method and device for server liquid cooling system | |
| CN117214775A (en) | Cable monitoring method and system based on parameter change rate | |
| CN116292332A (en) | Pump house inspection control method, system, readable storage medium and program product | |
| CN115171319A (en) | Electrical fire early warning system, method, electronic device and storage medium |
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 |