CN111503810A - Alarming method, device and terminal based on refrigerating unit performance alarming curved surface - Google Patents
Alarming method, device and terminal based on refrigerating unit performance alarming curved surface Download PDFInfo
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- CN111503810A CN111503810A CN201910093108.2A CN201910093108A CN111503810A CN 111503810 A CN111503810 A CN 111503810A CN 201910093108 A CN201910093108 A CN 201910093108A CN 111503810 A CN111503810 A CN 111503810A
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- 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
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- 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
- F24F11/52—Indication arrangements, e.g. displays
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- 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
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Abstract
The embodiment of the invention provides an alarming method, an alarming device and a terminal based on a refrigerating unit performance alarming curved surface. The embodiment of the invention extracts the historical steady-state working condition of the refrigerating unit based on the historical data of the refrigerating unit. And fitting a performance alarm curved surface based on the performance coefficients under the historical steady-state working conditions. The performance alarm curved surface is obtained based on data of the refrigerating unit in an actual operation environment, so that the accuracy is high. The accuracy of alarming based on the performance alarming curved surface with higher accuracy can be correspondingly improved.
Description
Technical Field
The invention relates to the technical field of abnormity diagnosis of heating ventilation air conditioners, in particular to an alarming method, an alarming device and a terminal based on a refrigerating unit performance alarming curved surface.
Background
The performance coefficient of the refrigerating unit of the heating ventilation air conditioner is influenced by external factors such as load, environment temperature, chilled water flow, cooling water flow, chilled water temperature, cooling water temperature and the like when the refrigerating unit works in a variable working condition and variable load running state for a long time.
When the refrigerating unit leaves a factory, a manufacturer can provide an alarm value of the performance coefficient of the refrigerating unit. In the operation process, if the performance coefficient of the refrigerating unit is lower than the alarm value, an alarm is triggered to remind operation and maintenance personnel to remove the fault of the refrigerating unit or adjust the setting parameters in time. However, the alarm value provided by the manufacturer is usually the performance coefficient in a standard test environment. And the actual operating environment (variable working condition and variable load) is usually greatly different from the standard test environment. The alarm is carried out based on the alarm value provided by the manufacturer, and the accuracy is not high.
Disclosure of Invention
The invention provides an alarming method, an alarming device and an alarming terminal based on a refrigerating unit performance alarming curved surface, aiming at solving the problem that the accuracy of the existing alarming based on an alarming value is not high.
In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect, the present invention provides an alarm method based on a performance alarm curved surface of a refrigeration unit, the method comprising:
acquiring historical data of each operating parameter of the refrigerating unit;
extracting historical steady-state working conditions of the refrigerating unit based on the historical data;
determining the performance coefficient of the refrigerating unit under each historical steady-state working condition;
fitting the refrigerating capacity, the ambient temperature and the performance coefficient of the refrigerating unit under each historical steady-state working condition by adopting a preset algorithm to obtain a performance alarm curved surface, wherein the performance alarm curved surface is used for representing the corresponding relation among the refrigerating capacity, the ambient temperature and the performance coefficient;
and if the current performance coefficient of the refrigerating unit is lower than a performance coefficient threshold value, alarming, wherein the performance coefficient threshold value is a performance coefficient corresponding to the current refrigerating capacity and the ambient temperature of the refrigerating unit on a performance alarm curved surface.
In a second aspect, the present invention provides an alarm device based on a performance alarm curved surface of a refrigeration unit, the device comprising:
the acquisition unit is used for acquiring historical data of each operating parameter of the refrigerating unit;
the extraction unit is used for extracting the historical steady-state working condition of the refrigerating unit based on the historical data;
the determining unit is used for determining the performance coefficient of the refrigerating unit under each historical steady-state working condition;
the system comprises a fitting unit, a performance alarm curved surface and a control unit, wherein the fitting unit is used for fitting the refrigerating capacity, the ambient temperature and the performance coefficient of the refrigerating unit under each historical steady-state working condition by adopting a preset algorithm to obtain the performance alarm curved surface, and the performance alarm curved surface is used for representing the corresponding relation among the refrigerating capacity, the ambient temperature and the performance coefficient;
and the alarm unit is used for giving an alarm if the current performance coefficient of the refrigerating unit is lower than a performance coefficient threshold value, wherein the performance coefficient threshold value is a performance coefficient corresponding to the current refrigerating capacity and the ambient temperature of the refrigerating unit on a performance alarm curved surface.
In a third aspect, the present invention provides a refrigeration unit performance alarm curved surface based alarm terminal comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: the alarm method based on the performance alarm curved surface of the refrigerating unit is realized.
In a fourth aspect, the present invention provides a machine-readable storage medium having stored thereon machine-executable instructions that, when executed by a processor, implement the above-described method for alarming based on a performance alarm curve of a refrigeration unit.
As can be seen from the above description, the embodiment of the present invention extracts the historical steady-state operating condition of the refrigeration unit based on the historical data of the refrigeration unit. And fitting a performance alarm curved surface based on the performance coefficients under the historical steady-state working conditions. The performance alarm curved surface is obtained based on data of the refrigerating unit in an actual operation environment, so that the accuracy is high. The accuracy of alarming based on the performance alarming curved surface with higher accuracy is correspondingly improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of an alarm method based on a performance alarm curve of a refrigeration unit according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating an implementation of step 102 according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a probability density curve of a chi-square distribution;
FIG. 4 is a schematic view of a sliding window shown in an embodiment of the present invention;
FIG. 5 is a flowchart illustrating an implementation of step 103 according to an embodiment of the present invention;
FIG. 6 is a flowchart illustrating an implementation of step 104 according to an embodiment of the present invention;
FIG. 7 is a schematic structural diagram of an alarm device based on a curved alarm surface for refrigerating unit performance according to an embodiment of the present invention;
fig. 8 is a schematic diagram of a hardware structure of an alarm terminal based on a curved alarm surface for performance of a refrigeration unit according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the embodiments of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used to describe various information in embodiments of the present invention, the information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, the negotiation information may also be referred to as second information, and similarly, the second information may also be referred to as negotiation information without departing from the scope of embodiments of the present invention. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
The embodiment of the invention provides an alarming method based on a refrigerating unit performance alarming curved surface. The method extracts the historical steady-state working condition of the refrigerating unit based on the historical data of the refrigerating unit. And fitting a performance alarm curved surface based on the performance coefficients under the historical steady-state working conditions. The performance alarm curved surface is obtained based on data of the refrigerating unit in an actual operation environment, so that the accuracy is high. The accuracy of alarming based on the performance alarming curved surface with higher accuracy is also correspondingly improved.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the following detailed description of the embodiments of the present invention is performed with reference to the accompanying drawings and specific embodiments:
referring to fig. 1, a flow chart of an alarm method based on a performance alarm curved surface of a refrigeration unit according to an embodiment of the present invention is provided.
As shown in fig. 1, the process may include the following steps:
In the concrete implementation, each operation parameter of the refrigerating unit is collected according to a preset sampling period. Wherein, each operation parameter may include: chilled water inlet temperature, chilled water outlet temperature, chilled water flow, cooling water inlet temperature, cooling water outlet temperature, cooling water flow, chiller power, and ambient temperature.
The historical data is the sampled value of each collected operation parameter.
And 102, extracting the historical steady-state working condition of the refrigerating unit based on the historical data of the operating parameters of the refrigerating unit.
In actual operation, the operating conditions of the refrigeration unit can change. The historical data recorded in step 101 includes data that the refrigeration unit has been operating under different operating conditions. According to the embodiment of the invention, each historical steady-state working condition of the refrigerating unit can be extracted by traversing the historical data.
Here, the steady-state operating condition refers to an operating state in which each operating parameter of the refrigeration unit tends to be stable for a period of time.
The process of determining the historical steady-state operating condition of the refrigeration unit according to the embodiments of the present invention is described below, and will not be described herein again.
And 103, determining the performance coefficients of the refrigerating unit under various historical steady-state working conditions.
The larger the performance coefficient is, the larger the output refrigerating capacity of the refrigerating unit under the unit power consumption is.
The process of determining the performance coefficient of the refrigeration unit under each historical steady-state working condition in the embodiments of the present invention is described in the following, and will not be described herein again.
And 104, fitting the refrigerating capacity, the ambient temperature and the performance coefficient of the refrigerating unit under each historical steady-state working condition by adopting a preset algorithm to obtain a performance alarm curved surface.
As an embodiment, the method can adopt a GA-BP (Genetic Algorithm-back propagation) model to fit the refrigerating output, the environment temperature and the performance coefficient under various historical steady-state working conditions to obtain a performance alarm curved surface.
For example, a GA-BP model with a 2-10-30-1 structure is adopted, namely an input layer is 2 nodes (refrigerating capacity and ambient temperature), an output layer is 1 node (performance coefficient), double hidden layers are 10 and 30 respectively, a tan sig function, an L ogsig function and a Purelin function are adopted as a transfer function, a trainrp is adopted as a training function, a learngdm is adopted as a weight value and threshold value learning algorithm, the iteration frequency of a genetic algorithm is 100 times, the population scale is 20, the cross probability is 0.4, the variation probability is 0.2, a floating point number code is adopted, the individual length is 4, and a performance alarm curved surface is obtained through model training and used for representing the corresponding relation of the refrigerating capacity, the ambient temperature and the performance coefficient.
Because the performance alarm curved surface is obtained based on the historical data of the refrigerating unit under each historical steady-state working condition, the performance coefficient of the refrigerating unit under each steady-state working condition can be truly reflected, and the accuracy is higher.
And 105, if the current performance coefficient of the refrigerating unit is lower than the performance coefficient threshold value, alarming.
Here, the performance coefficient threshold is a performance coefficient corresponding to the current cooling capacity and the ambient temperature of the refrigeration unit on the performance alarm curved surface.
According to the embodiment of the invention, the current performance coefficient of the refrigerating unit can be determined by acquiring the current operating parameters of the refrigerating unit. The current coefficient of performance is compared to a corresponding coefficient of performance threshold to determine whether an alarm is required.
If the current performance coefficient is lower than the corresponding performance coefficient threshold value, the current refrigeration performance is lower due to the fact that equipment faults or setting problems possibly exist in the refrigeration unit, and then an alarm is given out to prompt operation and maintenance personnel to process in time.
Thus, the flow shown in fig. 1 is completed.
As can be seen from the flow shown in fig. 1, the embodiment of the present invention extracts various historical steady-state operating conditions of the refrigeration unit based on historical data of the refrigeration unit. And fitting a performance alarm curved surface based on the performance coefficients under the historical steady-state working conditions. The performance alarm curved surface is obtained based on data of the refrigerating unit in an actual operation environment, so that the accuracy is high. The accuracy of alarming based on the performance alarming curved surface with higher accuracy is correspondingly improved.
The process of extracting the historical steady state operating conditions of the refrigeration unit in step 102 is described below. Referring to fig. 2, an implementation flow for determining historical steady-state operating conditions of a refrigeration unit is shown in an embodiment of the present invention.
As shown in fig. 2, the process may include the following steps:
step 201, determining a standard deviation threshold corresponding to each operation parameter.
When the refrigerating unit is in a steady-state working condition, the sampling values of all the operating parameters approximately follow normal distribution. The standard deviation of the normal distribution may reflect the degree of distribution of the sampling values. In general, the smaller the standard deviation, the more densely distributed the sampled values around the mean value, i.e., the more stable the operating parameters.
Based on this, embodiments of the present invention require determining a threshold for standard deviation that measures whether the operating parameter is stable.
The standard deviation formula for the operating parameters is as follows:
wherein:
n is the size of the sliding window, namely the number of sampling values of the ith operating parameter in the window;
xijsampling a jth sampling value of an ith operating parameter in the window;
siis the standard deviation of the ith operating parameter under the current window.
This equation (1) can be converted into:
wherein:
n is the size of the sliding window;
sithe standard deviation of the ith operation parameter under the current window is obtained;
σi 2is the overall variance of the ith operating parameter;
xijsampling a jth sampling value of an ith operating parameter in the window;
χ2(n-1) is a chi-square distribution with a degree of freedom of n-1.
As can be seen from the formula (2),
obeying a chi-square distribution with a degree of freedom of n-1.
Referring to fig. 3, a schematic diagram of a probability density curve of a chi-square distribution is shown. Wherein n represents a degree of freedom. Fig. 3 shows 3 chi-square distribution probability density curves with a degree of freedom of 1, a degree of freedom of 5, and a degree of freedom of 15, respectively.
The embodiment of the invention can determine the standard deviation threshold of the operation parameter based on the probability density of chi-square distribution. The method specifically comprises the following steps:
the overall mean square error of the operating parameter is determined. The overall mean square error is the mean square error determined based on all historical data of the operating parameters.
And acquiring the probability density of the operation parameters under the steady-state working condition. Under the condition of normal operation, most of the operating conditions are steady-state operating conditions, that is, most of historical data of the operating parameters tend to be stable, so that 99.5% of the historical data can be considered as data under the steady-state operating conditions. Namely the probability density of the running parameter of the refrigerating unit under the steady state working condition is 99.5 percent.
And determining a standard deviation threshold value corresponding to the operation parameter based on the probability density of the operation parameter under the steady-state working condition and the total mean square error of the operation parameter. The standard deviation threshold may be represented by the following formula:
wherein:
σiis the overall mean square error of the ith operating parameter;
θiand the standard deviation threshold value is corresponding to the ith operating parameter.
Step 202, judging whether the standard deviation of each operation parameter in the current window is smaller than the corresponding standard deviation threshold value, if so, turning to step 203; if not, go to step 204.
The embodiment of the invention utilizes the sliding window to traverse the historical data of each operating parameter of the refrigerating unit. As previously mentioned, the operating parameters of the refrigeration unit may include: chilled water inlet temperature, chilled water outlet temperature, chilled water flow, cooling water inlet temperature, cooling water outlet temperature, cooling water flow, chiller power, ambient temperature, and the like.
The embodiment of the invention calculates the standard deviation of each operation parameter in the current window by using a formula (1). The standard deviation of each operating parameter is then compared to the standard deviation threshold corresponding to each operating parameter determined in step 201.
If the standard deviation of each operation parameter is less than the corresponding standard deviation threshold value(s)i<θi) If the operation parameters in the current window tend to be stable, determining that the historical data in the current window belong to the historical data under the steady-state working condition, and turning to step 203; otherwise, it indicates that the historical data of the operating parameters in the current window is unstable, and the historical data in the current window does not belong to the historical data under the steady-state working condition, and go to step 204.
Step 203, slide to the next window, go to step 202.
Referring to fig. 4, a schematic diagram of a sliding window according to an embodiment of the present invention is shown. Where n is the window size.
And step 204, determining the historical data between the first window and the last window continuously traversed at this time as the historical data under the same historical steady-state working condition.
That is, when it is determined that the historical data in the current window is unstable through step 202, the historical data in several consecutive windows with stable data before the current window is determined as the historical data in the same historical stable condition, and the process goes to step 205.
Step 205, if the traversal of all the historical data is not completed, sliding to the next window, and going to step 202.
And repeatedly executing the step 202 to the step 205 until all history data traversals are completed.
Thus, the flow shown in fig. 2 is completed.
Through the process shown in fig. 2, a plurality of historical steady-state conditions can be extracted.
The process of determining the coefficient of performance of the refrigeration unit at each historical steady-state condition in step 103 is described below. Referring to fig. 5, an implementation flow for determining the performance coefficients under each historical steady-state operating condition is shown in the embodiment of the present invention.
As shown in fig. 5, the process may include the following steps:
step 501, obtaining the refrigerating capacity and the power consumption of the refrigerating unit under the current historical steady-state working condition.
As previously described, a plurality of historical steady-state conditions may be extracted from the historical data by the process illustrated in FIG. 2.
According to the embodiment of the invention, the performance coefficient of the refrigerating unit under the historical steady-state working condition is calculated for each historical steady-state working condition.
Specifically, the refrigerating capacity of the refrigerating unit under the current historical steady-state working condition is obtained. The cooling capacity can be expressed by the following formula:
wherein:
t1 is the starting time of the current historical steady-state condition;
t2 is the end time of the current historical steady state condition;
Qlds,ithe unit is kg/s of the instantaneous flow of the chilled water at the moment i;
tldsin,ithe temperature is the return water temperature of the chilled water at the moment i;
tldsout,ithe temperature is the water outlet temperature of the frozen water at the moment i;
t is a sampling period and the unit is s;
c is the specific heat capacity of the chilled water, and the unit kJ/(kg. DEG C)
And Q is the refrigerating capacity under the current historical steady-state working condition.
And acquiring the power consumption of the refrigerating unit under the current historical steady-state working condition. The power consumption can be expressed by the following formula:
wherein:
t1 is the starting time of the current historical steady-state condition;
t2 is the end time of the current historical steady state condition;
p is the instantaneous power of the refrigerating unit in kw;
t is a sampling period and is a unit of s;
and P is the power consumption under the current historical steady-state working condition.
Step 502, determining the performance coefficient of the refrigerating unit under the current historical steady-state working condition based on the refrigerating capacity and the power consumption.
The coefficient of performance of the refrigeration unit under the current historical steady-state operating condition can be expressed by the following formula:
cop Q/P formula (6)
Wherein:
q is the refrigerating capacity under the current historical steady-state working condition;
p is the power consumption under the current historical steady-state working condition;
cop is the coefficient of performance under the current historical steady-state operating condition.
The flow shown in fig. 5 is completed.
Through the process shown in fig. 5, the coefficient of performance of the refrigeration unit under each historical steady-state condition can be obtained.
The process of fitting the performance alarm surface in step 104 is described below. Referring to fig. 6, a flow for implementing a fitting performance alarm curved surface according to an embodiment of the present invention is shown.
As shown in fig. 6, the process may include the following steps:
step 601, dividing different working condition ranges according to the refrigerating capacity range and the environment temperature range of the refrigerating unit.
For example, the refrigerating capacity of the refrigerating unit ranges from 0% to 100% (percentage is used for representing the refrigerating capacity); the range of the ambient temperature is 21 to 40 degrees, and the range of the working condition can be divided according to the corresponding relation between the refrigerating capacity and the ambient temperature which possibly exist in the actual operation. For example, the refrigerating capacity is 0-10%, and the ambient temperature is 21 ℃ or 22 ℃, which are divided into a working condition range; the refrigerating capacity is 11-20%, the ambient temperature is 23 degrees or 24 degrees, the working condition range is divided, and the like.
Step 602, determining the working condition range to which each historical steady-state working condition belongs according to the refrigerating capacity and the ambient temperature of the refrigerating unit under each historical steady-state working condition.
As previously described, in step 501, the amount of refrigeration for the refrigeration unit at each historical steady-state condition has been calculated.
If the refrigerating capacity and the ambient temperature of the refrigerating unit under the historical steady-state working condition fall into a certain working condition range divided in the step 601, determining that the historical steady-state working condition belongs to the working condition range.
The working condition range of each historical steady-state working condition can be determined through the step.
Step 603, screening target performance coefficients from the performance coefficients of the refrigerating unit under each historical steady-state working condition in the same working condition range.
In actual operation, operation and maintenance personnel have different operation modes, which may cause a large difference in the performance coefficients of the refrigeration unit under each historical steady-state operating condition falling into the same operating condition range. According to the embodiment of the invention, a better performance coefficient (hereinafter referred to as a target performance coefficient) needs to be screened out aiming at each working condition range.
In the embodiment of the present invention, the process of screening the target performance coefficients may include: and traversing the performance coefficients of the refrigerating unit in the current working condition range from small to large. And if the traversed current performance coefficient is larger than the preset performance threshold value and the number of other performance coefficients larger than the current performance coefficient in the current working condition range is smaller than the preset number threshold value, determining that the current performance coefficient is the target performance coefficient, and stopping continuously traversing. The preset performance threshold is usually the minimum coefficient of performance that should be achieved.
For example, if there are 55 historical steady-state operating conditions falling within the current operating condition range, the number of the same performance coefficients is counted based on the performance coefficients of each historical steady-state operating condition, as shown in table 1.
TABLE 1
As can be seen from Table 1, the coefficient of performance over the current operating regime includes: 3.15, 3.75, 4.22, 4.51, 5.02. If the preset performance threshold is 3.5 and the preset number threshold is 10, the process of screening the target performance coefficient is as follows:
traversing the coefficient of performance 3.15, which is less than the performance threshold, the coefficient of performance 3.15 cannot be the target coefficient of performance.
Traversing coefficient of performance 3.75, which is greater than the performance threshold, the number of coefficients of performance greater than coefficient of performance 3.75 (10+6+3) is greater than the number threshold, and therefore coefficient of performance 3.75 cannot be the target coefficient of performance either.
And traversing the performance coefficient 4.22, wherein the performance coefficient is larger than the performance threshold, and the number (6+3) of the performance coefficients larger than the performance coefficient 4.22 is smaller than the number threshold, so that the performance coefficient 4.22 is taken as a target performance coefficient, and the traversal in the current working condition range is stopped.
It can be seen from the foregoing traversal process that, in the embodiment of the present invention, when a target performance coefficient is screened, a performance coefficient with a larger value is selected as much as possible (the performance coefficient is larger, the performance is better), but a performance coefficient with a larger value and a smaller occurrence number (which is accidental) can be filtered.
And step 604, fitting the refrigerating capacity, the ambient temperature and the target performance coefficient of the refrigerating unit under the historical steady-state working condition corresponding to each target performance coefficient by adopting a preset algorithm to obtain a performance alarm curved surface.
Because each target performance coefficient is the better performance coefficient screened out, the accuracy of the alarm performance curved surface fitted based on each target performance coefficient is higher.
The flow shown in fig. 6 is completed.
As can be seen from the flow shown in fig. 6, in the embodiment of the present invention, a better target performance coefficient is screened from the obtained performance coefficients under each historical steady-state working condition, so as to further improve the accuracy of the fitted performance alarm curved surface, and further improve the accuracy of the alarm based on the performance alarm curved surface.
The method provided by the embodiment of the invention is described above, and the device provided by the embodiment of the invention is described below:
fig. 7 is a schematic structural diagram of an apparatus according to an embodiment of the present invention. The device includes: an obtaining unit 701, an extracting unit 702, a determining unit 703, a fitting unit 704 and an alarming unit 705, wherein:
an obtaining unit 701, configured to obtain historical data of each operating parameter of the refrigeration unit;
an extracting unit 702, configured to extract a historical steady-state operating condition of the refrigeration unit based on the historical data;
a determining unit 703, configured to determine performance coefficients of the refrigeration unit under various historical steady-state operating conditions;
the fitting unit 704 is configured to fit the refrigeration capacity, the ambient temperature, and the performance coefficient of the refrigeration unit under each historical steady-state working condition by using a preset algorithm to obtain a performance alarm curved surface, where the performance alarm curved surface is used to represent a corresponding relationship between the refrigeration capacity, the ambient temperature, and the performance coefficient;
an alarm unit 705, configured to alarm if the current performance coefficient of the refrigeration unit is lower than a performance coefficient threshold, where the performance coefficient threshold is a performance coefficient corresponding to the current cooling capacity and the ambient temperature of the refrigeration unit on a performance alarm curved surface.
As an embodiment, the extracting unit 702 is specifically configured to determine a standard deviation threshold corresponding to each operating parameter; traversing historical data of operating parameters of the refrigeration unit by using a sliding window, and executing the following operations aiming at each window: if the standard deviation of each operation parameter in the current window is smaller than the corresponding standard deviation threshold value, sliding to the next window, and comparing the standard deviation of each operation parameter in the next window with the corresponding standard deviation threshold value; otherwise, determining the historical data between the first window and the last window continuously traversed at this time as the historical data under the same historical steady-state working condition; if not, sliding to the next window, and comparing the standard deviation of each operation parameter in the next window with the corresponding standard deviation threshold.
As an embodiment, the extracting unit 702 determines the standard deviation threshold corresponding to each operating parameter, including:
for each operating parameter, the following operations are performed:
determining the overall mean square error of the operation parameters, wherein the overall mean square error is determined based on all historical data of the operation parameters;
acquiring the probability density of the operation parameters under the steady-state working condition;
and determining a standard deviation threshold value corresponding to the operation parameter based on the probability density and the total mean square error.
As an embodiment, the determining unit 703 is specifically configured to, for each historical steady-state operating condition, perform the following operations: obtaining the refrigerating capacity and the power consumption of the refrigerating unit under the current historical steady-state working condition; and determining the performance coefficient of the refrigerating unit under the current historical steady-state working condition based on the refrigerating capacity and the power consumption.
As an embodiment, the fitting unit 704 is specifically configured to divide different working condition ranges according to a cooling capacity range and an ambient temperature range of the refrigeration unit; determining the working condition range to which each historical steady-state working condition belongs according to the refrigerating capacity and the ambient temperature of the refrigerating unit under each historical steady-state working condition; the following operations are performed for each operating condition range: screening target performance coefficients from the performance coefficients of the refrigerating unit under various historical steady-state working conditions in the same working condition range; and fitting the refrigerating capacity, the ambient temperature and the target performance coefficient of the refrigerating unit under the historical steady-state working condition corresponding to each target performance coefficient by adopting a preset algorithm to obtain a performance alarm curved surface.
As an embodiment, the fitting unit 704 filters the target performance coefficient from the performance coefficients of the refrigeration unit under the historical steady-state conditions in the same condition range, including:
traversing the performance coefficients of the refrigerating unit in the current working condition range from small to large;
and if the traversed current performance coefficient is larger than a preset performance threshold value, and the number of other performance coefficients larger than the current performance coefficient in the current working condition range is smaller than a preset number threshold value, determining that the current performance coefficient is a target performance coefficient, and stopping continuously traversing.
The description of the apparatus shown in fig. 7 is thus completed. The embodiment of the invention extracts the historical steady-state working condition of the refrigerating unit based on the historical data of the refrigerating unit. And fitting a performance alarm curved surface based on the performance coefficients of the refrigerating unit under the historical steady-state working conditions. The performance alarm curved surface is obtained based on data of the refrigerating unit in an actual operation environment, so that the accuracy is high. The alarming accuracy based on the performance alarming curved surface with higher accuracy can be correspondingly improved.
The following describes a terminal provided in an embodiment of the present invention:
fig. 8 is a schematic diagram of a hardware structure of a terminal according to an embodiment of the present invention. The terminal may include a processor 801, a machine-readable storage medium 802 having machine-executable instructions stored thereon. The processor 801 and the machine-readable storage medium 802 may communicate via a system bus 803. Also, the processor 801 may perform the above-described alarming method based on the refrigeration unit performance alarming curve by reading and executing machine executable instructions in the machine readable storage medium 802 corresponding to the alarming logic based on the refrigeration unit performance alarming curve.
The machine-readable storage medium 802 referred to herein may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and the like. For example, the machine-readable storage medium 802 may include at least one of the following storage media: volatile memory, non-volatile memory, other types of storage media. The volatile Memory may be a Random Access Memory (RAM), and the nonvolatile Memory may be a flash Memory, a storage drive (e.g., a hard disk drive), a solid state disk, and a storage disk (e.g., a compact disk, a DVD).
Embodiments of the present invention also provide a machine-readable storage medium, such as the machine-readable storage medium 802 in fig. 8, comprising machine-executable instructions that can be executed by the processor 801 in the terminal to implement the above-described alarm method based on the refrigerator group performance alarm curved surface.
Up to this point, the description of the terminal shown in fig. 8 is completed.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the embodiments of the present invention should be included in the scope of the present invention.
Claims (9)
1. An alarm method based on a refrigerating unit performance alarm curved surface is characterized by comprising the following steps:
acquiring historical data of each operating parameter of the refrigerating unit;
extracting historical steady-state working conditions of the refrigerating unit based on the historical data;
determining the performance coefficient of the refrigerating unit under each historical steady-state working condition;
fitting the refrigerating capacity, the ambient temperature and the performance coefficient of the refrigerating unit under each historical steady-state working condition by adopting a preset algorithm to obtain a performance alarm curved surface, wherein the performance alarm curved surface is used for representing the corresponding relation among the refrigerating capacity, the ambient temperature and the performance coefficient;
and if the current performance coefficient of the refrigerating unit is lower than a performance coefficient threshold value, alarming, wherein the performance coefficient threshold value is a performance coefficient corresponding to the current refrigerating capacity and the ambient temperature of the refrigerating unit on a performance alarm curved surface.
2. The method of claim 1, wherein extracting the historical steady state operating condition of the refrigeration unit based on the historical data comprises:
determining a standard deviation threshold value corresponding to each operation parameter;
traversing historical data of operating parameters of the refrigeration unit by using a sliding window, and executing the following operations aiming at each window:
if the standard deviation of each operation parameter in the current window is smaller than the corresponding standard deviation threshold value, sliding to the next window, and comparing the standard deviation of each operation parameter in the next window with the corresponding standard deviation threshold value; otherwise, determining the historical data between the first window and the last window continuously traversed at this time as the historical data under the same historical steady-state working condition;
if not, sliding to the next window, and comparing the standard deviation of each operation parameter in the next window with the corresponding standard deviation threshold.
3. The method of claim 2, wherein determining the standard deviation threshold for each operating parameter comprises:
for each operating parameter, the following operations are performed:
determining the overall mean square error of the operation parameters, wherein the overall mean square error is determined based on all historical data of the operation parameters;
acquiring the probability density of the operation parameters under the steady-state working condition;
and determining a standard deviation threshold value corresponding to the operation parameter based on the probability density and the total mean square error.
4. The method of claim 1, wherein determining the coefficient of performance of the refrigeration unit at each historical steady-state condition comprises:
for each historical steady-state condition, performing the following operations:
acquiring the refrigerating capacity and the power consumption of the refrigerating unit under the current historical steady-state working condition;
and determining the performance coefficient of the refrigerating unit under the current historical steady-state working condition based on the refrigerating capacity and the power consumption.
5. The method of claim 1, wherein fitting the refrigeration capacity, the ambient temperature, and the performance coefficient of the refrigeration unit under each historical steady-state condition using a preset algorithm to obtain a performance alarm curved surface comprises:
dividing different working condition ranges according to the refrigerating capacity range and the environment temperature range of the refrigerating unit;
determining the working condition range of each historical steady-state working condition according to the refrigerating capacity and the ambient temperature of the refrigerating unit under each historical steady-state working condition;
the following operations are performed for each operating condition range: screening target performance coefficients from the performance coefficients of the refrigerating unit under various historical steady-state working conditions in the same working condition range;
and fitting the refrigerating capacity, the ambient temperature and the target performance coefficient of the refrigerating unit under the historical steady-state working condition corresponding to each target performance coefficient by adopting a preset algorithm to obtain a performance alarm curved surface.
6. The method of claim 5, wherein the screening the target coefficient of performance from the coefficients of performance of the refrigeration unit at historical steady state conditions within the same range of conditions comprises:
traversing the performance coefficients of the refrigerating unit in the current working condition range from small to large;
and if the traversed current performance coefficient is larger than a preset performance threshold value, and the number of other performance coefficients larger than the current performance coefficient in the current working condition range is smaller than a preset number threshold value, determining that the current performance coefficient is a target performance coefficient, and stopping continuously traversing.
7. An alarm device based on a refrigerating unit performance alarm curved surface is characterized in that the device comprises:
the acquisition unit is used for acquiring historical data of each operating parameter of the refrigerating unit;
the extraction unit is used for extracting the historical steady-state working condition of the refrigerating unit based on the historical data;
the determining unit is used for determining the performance coefficient of the refrigerating unit under each historical steady-state working condition;
the system comprises a fitting unit, a performance alarm curved surface and a control unit, wherein the fitting unit is used for fitting the refrigerating capacity, the ambient temperature and the performance coefficient of the refrigerating unit under each historical steady-state working condition by adopting a preset algorithm to obtain the performance alarm curved surface, and the performance alarm curved surface is used for representing the corresponding relation among the refrigerating capacity, the ambient temperature and the performance coefficient;
and the alarm unit is used for giving an alarm if the current performance coefficient of the refrigerating unit is lower than a performance coefficient threshold value, wherein the performance coefficient threshold value is a performance coefficient corresponding to the current refrigerating capacity and the ambient temperature of the refrigerating unit on a performance alarm curved surface.
8. An alarm terminal based on a refrigeration unit performance alarm curved surface, the terminal comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: carrying out the method steps of any one of claims 1 to 6.
9. A machine-readable storage medium having stored therein machine-executable instructions which, when executed by a processor, perform the method steps of any of claims 1-6.
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