CN115111705B - Method, equipment and medium for detecting water flow bypass fault of water chilling unit - Google Patents
Method, equipment and medium for detecting water flow bypass fault of water chilling unit Download PDFInfo
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Abstract
Embodiments of the present disclosure relate to methods, apparatus, and media for detecting chiller water flow bypass faults. In the method, a plurality of temperature sampling data of a water chilling unit of a central air conditioner corresponding to a preset period are obtained; determining a similar proportion based on the plurality of temperature sampling data, wherein the similar proportion represents the proportion of the similar temperature sampling data in the plurality of temperature sampling data; determining whether the similar proportion meets a preset condition; and determining that the water chilling unit has a water flow bypass fault in response to determining that the similar proportion meets the predetermined condition. The method and the device can obviously improve the accuracy and the sensitivity of the water flow bypass fault detection.
Description
Technical Field
Embodiments of the present disclosure relate generally to the field of central air conditioning chiller fault detection, and more particularly to a method, apparatus, and medium for detecting chiller water flow bypass faults.
Background
During operation of the central air conditioning chiller, for example, a water bypass failure may occur. The reason for the occurrence of the water bypass failure may be, for example, that the water valve of the main unit is forgotten to close or cannot be completely closed, so that cooling water or chilled water still flows through the main unit after the main unit is shut down. When the water chilling unit has a water flow bypass fault, part of water flow flows through the host which is not operated, so that the water flow of the host which is operated is reduced, and the operation efficiency of the host which is operated is influenced. Or, in order to ensure that the water flow of the main machine is sufficient, the operation number of the pumps or the operation frequency of the pumps needs to be increased, so that the operation power consumption of the whole water chilling unit is obviously increased.
Currently, a water flow switch is typically used to check for the presence of a water flow bypass fault. For example, a water flow switch is provided in the chiller to detect whether water is flowing through the evaporator or condenser to determine if a water bypass condition exists in the non-operating main unit. There are at least two problems with the solution of using a water flow switch: first, when the bypass water flow is small (e.g., in the case of a valve not closed), the flow switch may not detect a flow bypass fault; second, the operating site fails to effectively monitor or conditions the water flow switch status, for example. Both of the two problems lead to lower accuracy and sensitivity of the current water flow bypass fault detection, and the water flow bypass fault is difficult to feed back in time.
In summary, in the conventional method for detecting the water flow bypass fault of the water chilling unit, a water flow switch is usually adopted for detection, and the problems of low accuracy and sensitivity exist.
Disclosure of Invention
In view of the above problems, the present disclosure provides a method, device and medium for detecting a water bypass fault of a chiller, which can significantly improve accuracy and sensitivity of water bypass fault detection.
According to a first aspect of the present disclosure, a method for detecting a chiller water flow bypass fault is provided. The method for detecting the water flow bypass fault of the water chilling unit comprises the following steps: acquiring a plurality of temperature sampling data of a water chilling unit of a central air conditioner corresponding to a preset period, wherein the plurality of temperature sampling data comprise inlet water temperature sampling data and outlet water temperature sampling data of a host which is not operated; determining a similar proportion based on the plurality of temperature sampling data, wherein the similar proportion represents the proportion of the similar temperature sampling data in the plurality of temperature sampling data; determining whether the similar proportion meets a preset condition; and determining that the water chilling unit has a water flow bypass fault in response to determining that the similar proportion meets the predetermined condition.
In some embodiments, determining the likeness score based on the plurality of temperature sample data comprises: determining a first temperature difference value of the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host machine based on the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host machine; determining whether the first temperature difference is less than a first threshold; in response to determining that the first temperature difference value is less than the first threshold, determining temperature sample data corresponding to the first temperature difference value as first similar temperature sample data to determine a first similar proportion based on a proportion of the first similar temperature sample data in the temperature sample data.
In some embodiments, determining the likeness score based on the plurality of temperature sample data comprises: and determining a correlation coefficient of the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host based on the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host, so as to determine a second similarity ratio based on the correlation coefficient.
In some embodiments, the plurality of temperature sample data further includes water inlet temperature sample data regarding the operating host and/or water inlet mains temperature sample data.
In some embodiments, determining the likeness score based on the plurality of temperature sample data comprises: determining a second temperature difference value based on the inlet water temperature sampling data and the outlet water temperature sampling data about the non-operating host and the difference value between the maximum value and the minimum value in the inlet water temperature sampling data about the operating host and/or the temperature sampling data of the water inlet main pipe; determining whether the second temperature difference is less than a second threshold; and in response to determining that the second temperature difference value is less than the second threshold, determining the temperature sample data corresponding to the second temperature difference value as second similar temperature sample data to determine a third similarity ratio based on a ratio of the second similar temperature sample data in the temperature sample data.
In some embodiments, determining the likeness score based on the plurality of temperature sample data comprises: and determining a correlation coefficient between a plurality of temperature sampling data in the inlet water temperature sampling data about the non-running host, the outlet water temperature sampling data, the inlet water temperature sampling data about the running host and the temperature sampling data of the inlet water main pipe, so as to determine a fourth similarity ratio based on the correlation coefficient.
In some embodiments, determining that the similar proportion satisfies the predetermined condition comprises: determining that the similarity score satisfies at least one of: determining that the first similar occupancy is greater than a first occupancy threshold; determining that the second similar occupancy is greater than a second occupancy threshold; determining that the third similar occupancy is greater than a third occupancy threshold; and determining that the fourth similar proportion is greater than a fourth proportion threshold.
According to a second aspect of the present disclosure, an electronic device is provided. The electronic device includes: at least one processing unit; at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions when executed by the at least one processing unit, cause the electronic device to perform the steps of the method according to the first aspect of the present disclosure.
According to a third aspect of the present disclosure, a computer-readable storage medium is provided. The computer readable storage medium has stored thereon a computer program which, when executed by a machine, implements a method according to the first aspect of the disclosure.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements.
Fig. 1 shows a schematic diagram of a computing device for implementing a method for detecting chiller water flow bypass faults according to an embodiment of the present disclosure.
Fig. 2 shows a flow chart of a method for detecting a chiller water flow bypass fault of an embodiment of the present disclosure.
Fig. 3 illustrates a flow chart of a method for determining a likeness score of an embodiment of the present disclosure.
Fig. 4 illustrates a flow chart of a method for determining a likeness score of an embodiment of the present disclosure.
Fig. 5 illustrates a flow chart of a method for determining a likeness score of an embodiment of the present disclosure.
Fig. 6 illustrates a flow chart of a method for determining a likeness score of an embodiment of the present disclosure.
Fig. 7 shows a schematic block diagram of an example electronic device that may be used to implement the method for detecting a chiller water flow bypass fault of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The term "including" and variations thereof as used herein is intended to be open-ended, i.e., "including but not limited to". Unless specifically stated otherwise, the term "or" means "and/or". The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
As described above, the conventional method for detecting the central air conditioning chiller only analyzes and diagnoses based on the operation parameter data at a single moment, and is prone to generate an erroneous detection result, and the accuracy is low.
To address at least in part one or more of the above problems and other potential problems, an example embodiment of the present disclosure proposes a solution to detect a central air conditioning chiller water flow bypass fault. According to the scheme, a plurality of temperature sampling data of the water chilling unit of the central air conditioner corresponding to the preset period are obtained, the temperature sampling data comprise water inlet temperature sampling data and water outlet temperature sampling data of a host which is not operated, and based on the temperature sampling data in the preset period, the error result caused by water flow bypass fault detection only according to the sampling data at a single moment can be avoided; then, based on the plurality of temperature sampling data, determining a similar proportion, wherein the similar proportion represents the proportion of the similar temperature sampling data in the plurality of temperature sampling data; determining whether the similar proportion meets a predetermined condition; and determining that the water chilling unit has a water flow bypass fault in response to determining that the similar proportion meets the predetermined condition. The similarity proportion shows the proximity degree of the corresponding inlet water temperature sampling data and outlet water temperature sampling data in the plurality of temperature sampling data, and the proximity degree has strong correlation with the water flow bypass fault, so that whether the water chilling unit has the water flow bypass fault or not is determined based on the similarity proportion, and the accuracy and the sensitivity are high.
Hereinafter, specific examples of the present scheme will be described in more detail with reference to the accompanying drawings.
Fig. 1 shows a schematic diagram of a computing device 100 for implementing a method for detecting chiller water flow bypass faults according to an embodiment of the present disclosure. The computing device 100 may have one or more Processing units, including special-purpose Processing units such as a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), and general-purpose Processing units such as a CPU (Central Processing Unit). In addition, one or more virtual machines may also be running on each computing device 100. In some embodiments, the computing device 100 includes, for example, a sample data acquisition unit 102, a similar proportion determination unit 106, a fault determination unit 108.
The sampling data acquiring unit 102 is configured to acquire a plurality of temperature sampling data corresponding to a predetermined period from a chiller of the central air conditioner. The plurality of temperature sampling data includes inlet water temperature sampling data and outlet water temperature sampling data about the non-operating host.
And a similar proportion determining unit 106 for determining a similar proportion based on the plurality of temperature sample data, the similar proportion characterizing the proportion of the similar temperature sample data in the plurality of temperature sample data.
A failure determination unit 108 for determining whether the similar duty ratio satisfies a predetermined condition; and determining that the water chilling unit has a water flow bypass fault in response to determining that the similar proportion meets the predetermined condition.
The following describes a method for detecting a chiller water flow bypass fault in accordance with an embodiment of the present disclosure. Fig. 2 illustrates a flow diagram of a method 200 for detecting a chiller water flow bypass fault of an embodiment of the present disclosure. The method 200 may be performed by the computing device 100 as shown in FIG. 1, or may be performed at the electronic device 800 shown in FIG. 7. It should be understood that method 200 may also include additional steps not shown and/or may omit steps shown, as the scope of the present disclosure is not limited in this respect.
At step 202, a computing device obtains a plurality of temperature sample data for a chiller of a central air conditioner corresponding to a predetermined period. The plurality of temperature sample data includes, for example, inlet water temperature sample data and outlet water temperature sample data for an un-operating host.
In some embodiments, the plurality of temperature sample data further includes, for example, water inlet temperature sample data regarding the operating host and/or water inlet mains temperature sample data.
Regarding the predetermined period, the time length thereof can be set reasonably according to actual needs. To achieve both efficiency and accuracy, in some embodiments, the predetermined period of time is, for example, no less than 1 hour, and no greater than 48 hours in length. To increase the effectiveness of the incoming water temperature sample data, outgoing water temperature sample data, incoming water temperature sample data, and incoming water header temperature sample data for the inactive host over a predetermined period, in some embodiments, the start time of the predetermined period, e.g., the time of shutdown from the target inactive host, is greater than or equal to 30 minutes. In some embodiments, when the target non-operating host is in a non-operating state (i.e., a shutdown state), at least one host in the chiller is in an operating state.
It should be appreciated that by detecting whether a water bypass fault exists in the chiller based on a plurality of temperature sample data over a predetermined period, erroneous results from detection based on temperature sample data at a single time may be avoided.
At step 206, the computing device determines a likeness score based on the plurality of temperature sample data. The similar proportion characterizes a proportion of similar temperature sample data among the plurality of temperature sample data.
The similarity ratio includes, for example, at least one of a first similarity ratio, a second similarity ratio, a third similarity ratio, and a fourth similarity ratio. First and second similar ratios, e.g., associated with inlet and outlet water temperature sample data for non-operating hosts; the third and fourth similar ratios are, for example, associated with inlet and outlet water temperature sample data for non-operating hosts, and inlet water temperature sample data and/or inlet mains temperature sample data for operating hosts.
As to the method of determining the similarity ratio, it includes, for example: the computing device determines a first temperature difference value of the inlet water temperature sampling data and the outlet water temperature sampling data of the non-operating host based on the inlet water temperature sampling data and the outlet water temperature sampling data of the non-operating host; determining whether the first temperature difference is less than a first threshold; and in response to determining that the first temperature difference value is less than the first threshold, determining temperature sample data corresponding to the first temperature difference value as first similar temperature sample data to determine a first similar proportion based on a proportion of the first similar temperature sample data in the temperature sample data. The method for determining the similarity ratio will be described in detail below with reference to fig. 3 to 6, and will not be described herein again.
At step 208, the computing device determines whether the similar proportions satisfy a predetermined condition.
In some embodiments, determining that the similar proportion satisfies the predetermined condition includes, for example: determining that the similar proportion satisfies at least one of: determining that the first similar proportion is greater than a first proportion threshold; determining that the second similar ratio is greater than a second ratio threshold; determining that the third similar occupancy is greater than a third occupancy threshold; and determining that the fourth similar proportion is greater than a fourth proportion threshold. The first, second, third and fourth occupation ratio thresholds correspond to the first, second, third and fourth similar occupation ratios, respectively.
At step 210, if the computing device determines that the similar ratio satisfies the predetermined condition, the computing device determines that a water chiller has a water bypass fault.
For example, if the computing device determines that the first similar proportion is greater than the first proportion threshold, or the second similar proportion is greater than the second proportion threshold, or the third similar proportion is greater than the third proportion threshold, or the fourth similar proportion is greater than the fourth proportion threshold, the computing device determines that the central air conditioning chiller has a water flow bypass fault.
At step 212, if the computing device determines that the similar ratio does not satisfy the predetermined condition, the computing device determines that the central air conditioning chiller does not have a flow bypass fault. For example, if the computing device determines that the first similar duty ratio is less than or equal to a first duty ratio threshold, the second similar duty ratio is less than or equal to a second duty ratio threshold, the third similar duty ratio is less than or equal to a third duty ratio threshold, and the fourth similar duty ratio is less than or equal to a fourth duty ratio threshold, the computing device determines that the central air conditioning chiller does not have a water bypass fault.
In the scheme, whether the water chilling unit has the fault of the computing equipment or not is determined according to the similarity proportion, and the accuracy and the sensitivity are high. It should be appreciated that, for example, corresponding inlet and outlet water temperature sample data for the non-operating host are determined to be similar temperature sample data, indicating that the corresponding inlet and outlet water temperature sample data for the non-operating host are very close, whereas the similarity represents, for example, the overall proximity of the corresponding inlet and outlet water temperature sample data for the non-operating host over a predetermined period. That is, the higher the similarity score, the higher the closeness of the entirety of the corresponding inlet water temperature sample data and outlet water temperature sample data with respect to the non-operating host, for example, in a predetermined period. This proximity has a high correlation with the flow bypass fault, and therefore, if the similar duty ratio satisfies a predetermined condition (e.g., is greater than a predetermined threshold), it can be determined that the chiller has the flow bypass fault, which is highly accurate and sensitive. Moreover, by using the similar ratio in the preset period instead of the single temperature sampling data as the basis for judging whether the water flow bypass fault exists, the false alarm caused by the uncertainty or error of the single temperature sampling data can be avoided.
Fig. 3 illustrates a flow diagram of a method 400 for determining a likeness score of an embodiment of the present disclosure. The method 400 may be performed by the computing device 100 as shown in FIG. 1, or may be performed at the electronic device 800 shown in FIG. 7. It should be understood that method 400 may also include additional steps not shown and/or may omit steps shown, as the scope of the disclosure is not limited in this respect.
At step 402, the computing device determines a first temperature difference value for the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host based on the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host.
For example, the leaving water temperature sample data for a non-running host is from a first leaving water temperature sample sequence and the entering water temperature sample data for a non-running host is from a first entering water temperature sample sequence. The first outlet water temperature sampling sequence comprises a plurality of first outlet water temperature sampling data, and the first inlet water temperature sampling sequence comprises a plurality of first inlet water temperature sampling data. For example, the first outlet water temperature sampling sequence is characterized by { T1_ out _1, T1_ out _2, T1_ out _3, \ 8230 \ 8230and T1_ out _ n }, wherein T1_ out _ i represents ith first outlet water temperature sampling data; the first inlet water temperature sampling sequence is characterized as { T1_ in _1, T1_ in _2, T1_ in _3, \ 8230 \ 8230and T1_ in _ n }, wherein T1_ in _ i represents ith first inlet water temperature sampling data, and i represents ith first inlet water temperature sampling data
[1，n]。
For example, the computing device derives a first temperature difference sequence from the first leaving water temperature sampling sequence and the first entering water temperature sampling sequence to derive a plurality of first temperature difference values. First temperature difference sequenceE.g. characterized as
T1_1，
T1_2，……
T1_ n, wherein,
T1_1=T1_out_1-T1_in_1，
T1_2=T1_out_3-T1_in_3，……
t1_ n = T1_ out _ n-T1_ in _ n, wherein,
t1_ i represents the ith first temperature difference, i
[1，n]And n is the number of first temperature difference values in the first temperature difference sequence.
In some embodiments, the first outlet water temperature sampling data is, for example, temperature sampling data about a cooling water outlet of the non-operating host, which is acquired by using a temperature sensor disposed at the cooling water outlet (e.g., a water outlet of a condenser) of the non-operating host; the first intake water temperature sampling data is temperature sampling data about a cooling water inlet of the non-operating host, which is acquired by a temperature sensor provided at a cooling water inlet (e.g., a water inlet of a condenser) of the operating host.
In some embodiments, the first outlet water temperature sampling data is, for example, temperature sampling data about a chilled water outlet of a non-operating host, which is acquired by using a temperature sensor provided at the chilled water outlet of the non-operating host (for example, a water outlet of an evaporator); the first inlet water temperature sampling data is temperature sampling data about a chilled water inlet of a non-operating host, which is acquired by a temperature sensor provided at the chilled water inlet of the non-operating host (e.g., a water inlet of an evaporator).
At step 404, the computing device determines whether the first temperature difference value is less than a first threshold.
At step 406, if the computing device determines that the first temperature difference value is less than the first threshold, the computing device determines temperature sample data corresponding to the first temperature difference value as first similar temperature sample data to determine a first similar occupancy based on an occupancy of the first similar temperature sample data in the temperature sample data.
At step 408, if the computing device determines that the first temperature difference is greater than or equal to the first threshold, the computing device determines that the temperature sample data corresponding to the first temperature difference is not similar.
When a flow bypass fault occurs, the inlet water temperature and outlet water temperature of the non-operating host are theoretically the same. In consideration of the heat transfer in the chiller, the detection accuracy of the temperature sensor, and other factors, in some embodiments, the first threshold is in a range of 0.1-1 ℃. If the first threshold is too large, for example, greater than 1 ℃, a false alarm is easily caused; if the first threshold value is too small, for example, less than 0.1 ℃, a false alarm may be easily caused because the measurement accuracy of the temperature sensor cannot achieve such a high accuracy.
For example, the computing device compares the first temperature difference value
T1_i（i
[1，n]) Comparing the temperature difference values with a first threshold value one by one to determine a first temperature difference value
T1_ i is less than the first threshold. If it is firstA difference in temperature
T1_ i is less than the first threshold, indicating a first temperature difference
If the numerical values of the first water outlet temperature sampling data T1_ out _ i corresponding to the first water outlet temperature T1_ i and the first water inlet temperature sampling data T1_ in _ i are close enough, the computing device determines that the first water outlet temperature sampling data T1_ out _ i and the first water inlet temperature sampling data T1_ in _ i are first similar temperature sampling data; if the first temperature difference value
T1_ i is greater than or equal to the first threshold, which indicates that the value difference between the first outlet temperature sample data T1_ out _ i and the first inlet temperature sample data T1_ in _ i is large, and the computing device determines that the first outlet temperature sample data T1_ out _ i is not similar to the first inlet temperature sample data T1_ in _ i. Traversing all the first temperature difference values
T1_i（i
[1，n]) Thereafter, the computing device obtains the number of first similar temperature sample data, which is set as j1.
At step 410, the computing device determines a first similar proportion based on the proportion of the first similar temperature sample data in the temperature sample data.
For example, if the number of the first similar temperature sample data is j1, the first similar ratio r1= j1/n.
After obtaining the first similar proportion, the computing device determines whether the first similar proportion is greater than a first proportion threshold. If the first similar proportion is larger than the first proportion threshold value, the computing equipment determines that a water flow bypass fault exists in the central air conditioner water chilling unit, for example, a water flow bypass fault alarm is sent out; if the first similar proportion is determined to be less than or equal to the first proportion threshold value, the computing device determines that the central air conditioning chiller does not have a water flow bypass fault, for example, a water flow bypass fault alarm is not sent out.
In the above scheme, whether the water flow bypass fault exists is detected based on the difference in inlet and outlet water temperatures (e.g., a first temperature difference) of the non-operating host machine. When the first temperature difference value is smaller than the first threshold value, it is indicated that the temperature difference between the inlet water and the outlet water of the host which is not operated is small, and under the condition that other operating hosts exist at the same time, the temperature sampling data corresponding to the first temperature difference value can be determined to be close enough, and can be determined as first similar temperature sampling data. Therefore, the water flow bypass fault can be accurately detected, and the precision is higher. And, the temperature sampling data for obtaining the first temperature difference can be acquired based on the temperature sensor arranged at the relevant water inlet and outlet of the water chilling unit, and the temperature sensor is convenient to set. In some embodiments, the temperature sensor arrangement of the related water inlet and outlet of the water chilling unit can be utilized, so that the cost can be effectively saved. Moreover, the scheme can be suitable for diagnosis in the process of monitoring the states of the small flow and the water flow switch.
It should be understood that the presence of, for example, the first similar temperature sample data among the plurality of temperature sample data indicates that there is a case where the first outlet temperature sample data T1_ out _ i is sufficiently close to the first inlet temperature sample data T1_ in _ i. However, if the first outlet temperature sampling data T1_ out _ i and the first inlet temperature sampling data T1_ in _ i corresponding to a single sampling point are only used for judgment, a false alarm is easily generated, which brings unnecessary trouble to the user. And if the first similar proportion is larger than the first proportion threshold, the situation that the first water outlet temperature sampling data T1_ out _ i and the first water inlet temperature sampling data T1_ in _ i are close enough in a preset period reaches a certain severity, in the scheme, the water flow bypass fault of the central air-conditioning water chilling unit is determined, and the judgment result is more accurate and reliable.
Regarding the first proportion threshold, for example, the value range may be 70% -90%, and may also be set reasonably according to historical statistical data.
Fig. 4 illustrates a flow chart of a method 500 for determining a likeness score of an embodiment of the present disclosure. The method 500 may be performed by the computing device 100 as shown in FIG. 1, or may be performed at the electronic device 800 shown in FIG. 7. It should be understood that method 500 may also include additional steps not shown and/or may omit steps shown, as the scope of the present disclosure is not limited in this respect.
At step 502, the computing device determines correlation coefficients for the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host based on the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host to determine a second similar ratio based on the correlation coefficients.
At step 504, the computing device determines a second similar proportion based on the correlation coefficient.
In some embodiments, the correlation coefficient for the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host is determined with reference to equation (1) as follows:
wherein, CORT (X) T ,Y T ) Characterizing the correlation coefficient of the inlet and outlet temperature sample data with respect to the non-operating host, i.e., the first outlet temperature sample sequence (assumed to be X) T Characterization) and a first inlet water temperature sampling sequence (assumed to be Y) T Characterization) of the correlation coefficient; x is a radical of a fluorine atom t+1 And x t The first outlet water temperature sampling data respectively correspond to two adjacent first outlet water temperature sampling data in the first outlet water temperature sampling sequence, such as T1_ out _ T +1 and T1_ out _ T; y is t+1 And y t The first intake water temperature sampling sequences respectively correspond to two first intake water temperature sampling data adjacent to each other in front and back, for example, T1_ in _ T +1 and T1_ in _ T.
It should be understood that when CORT (X) T ,Y T ) When =1, it indicates that the first outlet water temperature sampling sequence and the first inlet water temperature sampling sequence have the same variation trend, for example, the first outlet water temperature sampling sequence and the first inlet water temperature sampling sequenceThe temperature sampling sequences rise or fall simultaneously along with time, and the change amplitudes are also the same; when CORT (X) T ,Y T ) When =1, it is characterized that the first outlet water temperature sampling sequence and the first inlet water temperature sampling sequence have opposite variation trends, for example, the first outlet water temperature sampling sequence and the first inlet water temperature sampling sequence vary inversely with time, which is equal to zero, and the variation amplitudes are also the same; when CORT (X) T ,Y T ) And when the value is =0, no correlation exists between the change of the first outlet water temperature sampling sequence and the change of the first inlet water temperature sampling sequence.
After a water chilling unit is operated for a long time, a detection device (such as a temperature sensor) arranged in the water chilling unit may form a certain fixed deviation. For example, for the same measured temperature, a first temperature sensor arranged at a first position (for example, a chilled water outlet of a non-operating host) detects a value a, and a second temperature sensor arranged at a second position (for example, a chilled water inlet of a non-operating host) detects a value B, where a and B are not equal; however, the difference between a and B is fixed for the same measured temperature. At this time, it should be considered that there is a fixed error between the first temperature sensor and the second temperature sensor. At this time, if whether a water flow bypass fault exists in the water chilling unit is judged only according to the difference value of the values detected by the first temperature sensor and the second temperature sensor, a condition of alarm leakage may occur.
Therefore, in the above scheme, the influence of the fixed error on the detection result can be effectively avoided by introducing the correlation coefficient as the second similar proportion. The correlation coefficient shows convergence of the change trend of the data in the two temperature sampling sequences along with time. If the correlation coefficient is higher, the change trends of at least two temperature sampling sequences are converged in most of time; the low correlation coefficient indicates that the variation trends of the at least two temperature sampling sequences converge only in a few times, the variation trends in most times are different, even the variation trends have no correlation, or the variation trends in the opposite case exist. Therefore, in the detection process for the water flow bypass fault, the correlation coefficient can show the proportion of similar data in the two temperature sampling sequences. When the second similar proportion is larger than the second proportion threshold (for example, the second proportion threshold is 0.7), the change trends of the two temperature sampling sequences are converged most of the time, and the water flow bypass fault of the water chilling unit can be determined according to the change trends. The correlation coefficient is not influenced by the fixed error, so that the scheme can normally play a role no matter whether the fixed error exists or not, and the accuracy of detecting the water flow bypass fault can be improved.
Fig. 5 illustrates a flow chart of a method 600 for determining a likeness score of an embodiment of the present disclosure. The method 600 may be performed by the computing device 100 as shown in FIG. 1, or may be performed at the electronic device 800 shown in FIG. 7. It should be understood that method 600 may also include additional steps not shown and/or may omit steps shown, as the scope of the disclosure is not limited in this respect.
To improve the accuracy of flow bypass fault detection, in some embodiments, the plurality of temperature samples further includes water inlet temperature samples for the operating host and/or water inlet manifold temperature samples. Accordingly, the plurality of temperature sample data further includes water inlet temperature sample data regarding the operating host and/or water inlet mains temperature sample data.
At step 602, the computing device determines a second temperature difference value based on a difference between a maximum value and a minimum value of the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host and the inlet water temperature sample data and/or the inlet mains temperature sample data for the operating host.
For example, the leaving water temperature sample data for a non-running host is from a first leaving water temperature sample sequence and the entering water temperature sample data for a non-running host is from a first entering water temperature sample sequence. The first outlet water temperature sampling sequence comprises a plurality of first outlet water temperature sampling data, and the first inlet water temperature sampling sequence comprises a plurality of first inlet water temperature sampling data. For example, the first outlet water temperature sampling sequence is characterized by { T1_ out _1, T1_ out _2, T1_ out _3, \ 8230 \ 8230and T1_ out _ n }, wherein T1_ out _ i represents the ith first outlet water temperature sampling sequenceSample data; the first inlet water temperature sampling sequence is characterized as { T1_ in _1, T1_ in _2, T1_ in _3, \8230 \ 8230and T1_ in _ n }, wherein T1_ in _ i represents the ith first inlet water temperature sampling data, and i represents the ith first inlet water temperature sampling data
[1，n]。
For example, the inlet water temperature sample data for the running host is from a second inlet water temperature sample sequence. The second inlet water temperature sampling sequence comprises a plurality of second inlet water temperature sampling data. For example, the second influent water temperature sample sequence is characterized as { T2_ in _1, T2_ in _2, T2_ in _3, \8230, T2_ in _ n }, wherein T2_ in _ i represents the ith second influent water temperature sample data, i
[1，n]. With respect to the operational hosts, in some embodiments, when more than one operational host is present, for example, corresponding inlet water temperature sample data for all operational hosts is traversed for diagnosing whether a water bypass fault exists for the non-operational host.
The temperature sampling data of the water inlet main is from a water inlet main temperature sampling sequence. The sequence of water intake mains temperature samples is characterized for example by { T3_ in _1, T3_ in _2, T3_ in _3, \8230; T3_ in _ n }, wherein T3_ in _ i characterizes the temperature sample data of the ith water intake mains, i
[1，n]. And the temperature sampling data of the water inlet main pipe is acquired by utilizing a temperature sensor arranged on the water inlet main pipe of the running host.
The computing device determines a second sequence of temperature differences based on the inlet water temperature sample data and the outlet water temperature sample data for the non-operating host and a difference between a maximum value and a minimum value in the inlet water temperature sample data and/or the inlet mains temperature sample data for the operating host to determine a plurality of second temperature difference values. With respect to the second temperature difference sequence, which is characterized, for example, as T3_1,
T3_2，……
t3_ n, wherein,
t3_ i represents the ith second temperature difference, i
[1，n]And n is the number of second temperature difference values in the second temperature difference sequence.
In some embodiments, the second temperature difference is derived based on, for example, the inlet water temperature sample data for the non-operating host, the outlet water temperature sample data for the non-operating host, and the inlet manifold temperature sample data. At this time, the process of the present invention,
T3_i=max(T1_out_i, T1_in_i, T3_in_i)-min(T1_out_i, T1_in_i, T3_in_i)，i
[1，n]. Wherein max () represents taking the maximum value to operate, and min () represents taking the minimum value to operate.
In some embodiments, the second temperature difference is derived based on, for example, the inlet water temperature sample data for the non-operating host, the outlet water temperature sample data for the non-operating host, and the inlet water temperature sample data for the operating host. At this time, the process of the present invention,
T3_i=max(T1_out_i, T1_in_i, T2_in_i)-min(T1_out_i, T1_in_i, T2_in_i)，i
[1，n]。
in some embodiments, the second temperature difference is based on, for example, the inlet water temperature sampling data of the non-operating host, the outlet water temperature sampling data of the non-operating host, the inlet water temperature sampling data with respect to the operating host, and the temperature of the inlet manifoldThe data is sampled. At this time, the process of the present invention,
T3_i=max(T1_out_i, T1_in_i, T2_in_i，T3_in_i)-min(T1_out_i, T1_in_i，T2_in_i，T3_in_i)，i
[1，n]。
at step 604, the computing device determines whether the second temperature difference is less than a second threshold.
At step 606, if the computing device determines that the second temperature difference value is less than the second threshold, the computing device determines temperature sample data corresponding to the second temperature difference value as second similar temperature sample data to determine a third similar occupancy based on an occupancy of the second similar temperature sample data in the temperature sample data.
At step 608, if the computing device determines that the second temperature difference is greater than or equal to the second threshold, the computing device determines that the temperature sample data corresponding to the second temperature difference is not similar.
At step 610, the computing device determines a third similar occupancy ratio based on the occupancy ratio of the second similar temperature sample data in the temperature sample data.
For example, assuming that the number of the second similar temperature sample data is j2, the third similar duty ratio r2= j2/n.
In some embodiments, a reasonable range for the third threshold is, for example, 0.1-1 ℃. If the third threshold is too large, for example, greater than 1 ℃, a false alarm is easily caused; if the third threshold is too small, for example, less than 0.1 ℃, a false alarm may be easily caused because the measurement accuracy of the temperature sensor cannot reach such a high accuracy.
After obtaining the third likeness, the computing device determines whether the third likeness is greater than a third ratio threshold. If the third similar proportion is larger than the third proportion threshold value, determining that the central air-conditioning water chilling unit has a water flow bypass fault, for example, sending a water flow bypass fault alarm; and if the third similar occupancy is determined to be less than or equal to the third occupancy threshold, determining that the central air-conditioning water chilling unit has no water flow bypass fault.
With respect to the running hosts, in some embodiments, when more than one running host is used, for example, corresponding inlet water temperature sample data of all running hosts is traversed for diagnosing whether a water bypass fault exists in the non-running host. For example, the water inlet temperature sampling data of each running host is respectively used as a second water inlet temperature sampling sequence to diagnose whether the water flow bypass fault exists in the non-running host. If each running host is taken as a reference, a result that the third similar occupation ratio is smaller than or equal to a third occupation ratio threshold value can be obtained, and it is determined that the central air-conditioning water chilling unit has no water flow bypass fault; otherwise, as long as the third similar proportion is larger than the third proportion threshold value by taking any one of the operating main machines as a reference, determining that the central air-conditioning water chilling unit has a water flow bypass fault, and determining that the water flow bypass fault occurs between the corresponding operating main machine and the diagnosed non-operating main machine.
In the scheme, the water inlet temperature sampling data and the water outlet temperature sampling data of the host which is not operated, the water inlet temperature sampling data of the host which is operated and/or the temperature sampling data of the water inlet main pipe and other multiple temperature sampling data are combined for comprehensive calculation to form a second temperature difference value, the temperature difference conditions of multiple different related water inlets and water outlets in the water chilling unit can be reflected more accurately, whether a water flow bypass fault exists in the water chilling unit or not is determined according to the temperature difference conditions, and the accuracy is higher. And, the temperature sampling data for obtaining the second temperature difference can be acquired based on the temperature sensor arranged at the relevant water inlet and outlet of the water chilling unit, and the temperature sensor is convenient to set. In some embodiments, the temperature sensor arrangement can be realized by using the temperature sensor arrangement already arranged at the relevant water inlet and outlet of the water chilling unit, so that the cost can be effectively saved.
Fig. 6 illustrates a flow chart of a method 700 for determining a likeness score of an embodiment of the present disclosure. The method 700 may be performed by the computing device 100 as shown in FIG. 1, or may be performed at the electronic device 800 shown in FIG. 7. It should be understood that method 700 may also include additional steps not shown and/or may omit steps shown, as the scope of the disclosure is not limited in this respect.
At step 702, the computing device determines a correlation coefficient between a plurality of temperature sample data of the inlet water temperature sample data for the non-operating host, the outlet water temperature sample data, the inlet water temperature sample data for the operating host, and the temperature sample data for the inlet manifold.
In some embodiments, a correlation coefficient between any two of the first leaving water temperature sample sequence, the first entering water temperature sample sequence, the second entering water temperature sample sequence, and the intake manifold temperature sample sequence is determined to obtain a plurality of correlation coefficients.
At step 704, the computing device determines a fourth similarity ratio based on the correlation coefficient.
In some embodiments, the computing device obtains a minimum value of the plurality of correlation coefficients as a fourth similarity ratio. In some embodiments, the computing device obtains an average of the plurality of correlation coefficients as a fourth similar proportion.
After obtaining the fourth similar proportion, the computing device calculates whether the fourth similar proportion is greater than a fourth proportion threshold. If the fourth similar proportion is larger than the fourth proportion threshold value, the computing equipment determines that a water flow bypass fault exists in the central air-conditioning water chilling unit; if the fourth similar proportion is determined to be smaller than or equal to or larger than the fourth proportion threshold value, the computing device determines that the central air-conditioning water chilling unit has a water flow bypass fault.
In the scheme, a plurality of correlation coefficients corresponding to a plurality of temperature sampling data are obtained so as to determine whether the water chilling unit has a water flow bypass fault, and the detection accuracy is higher.
Fig. 7 shows a schematic block diagram of an example electronic device 800 that may be used to implement the method for detecting a chiller water flow bypass fault of an embodiment of the present disclosure. As shown, electronic device 800 includes a central processing unit (i.e., CPU 801) that can perform various appropriate actions and processes in accordance with computer program instructions stored in a read-only memory (i.e., ROM 802) or loaded from storage unit 808 into a random access memory (i.e., RAM 803). In the RAM 803, various programs and data required for the operation of the electronic apparatus 800 can also be stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input/output interface (i.e., I/O interface 805) is also connected to bus 804.
A number of components in the electronic device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, a microphone, and the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the electronic device 800 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
Various processes and processes described above, such as methods 200, 300, 400, 500, 600, and 700, may be performed by the CPU 801. For example, in some embodiments, methods 200, 300, 400, 500, 600, and 700 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto the electronic device 800 via the ROM 802 and/or the communication unit 809. When loaded into RAM 803 and executed by CPU 801, a computer program may perform one or more of the acts of methods 200, 300, 400, 500, 600, and 700 described above.
The present disclosure relates to methods, apparatuses, systems, electronic devices, computer-readable storage media and/or computer program products. The computer program product may include computer-readable program instructions for performing various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be interpreted as a transitory signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or an electrical signal transmitted through an electrical wire.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge computing devices. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The method and the device have the advantages that based on the deep analysis of the influence of the water flow bypass fault, the key parameters capable of representing the fault are extracted, the key parameters can be based on basic data collected by a water chilling unit, such as temperature and the like, and therefore diagnosis can be achieved without adding equipment. The key parameter can be used for representing the small-flow bypass fault, and has better universality. According to the fault diagnosis method and device, the fault diagnosis result is not based on data obtained at a certain moment, but data in a period of time are comprehensively judged, and the diagnosis accuracy rate can be improved.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (8)
1. A method for detecting a chiller water flow bypass fault, comprising:
acquiring a plurality of temperature sampling data of a water chilling unit of a central air conditioner corresponding to a preset period, wherein the plurality of temperature sampling data comprise water inlet temperature sampling data and water outlet temperature sampling data about a host which is not operated;
determining a similar proportion based on the plurality of temperature sampling data, wherein the similar proportion represents the proportion of the similar temperature sampling data in the plurality of temperature sampling data;
determining whether the similar proportion meets a preset condition; and
in response to determining that the similar proportion meets a predetermined condition, determining that a water flow bypass fault exists in the water chilling unit;
wherein determining the similarity score based on the plurality of temperature sample data comprises:
determining a first temperature difference value of the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host machine based on the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host machine;
determining whether the first temperature difference is less than a first threshold; and
in response to determining that the first temperature difference value is less than the first threshold, the temperature sample data corresponding to the first temperature difference value is determined to be first similar temperature sample data, such that the first similar duty ratio is determined based on a duty ratio of the first similar temperature sample data in the temperature sample data.
2. The method of claim 1, wherein determining the likeness score based on the plurality of temperature sample data comprises:
and determining a correlation coefficient of the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host based on the inlet water temperature sampling data and the outlet water temperature sampling data of the non-running host, so as to determine a second similarity ratio based on the correlation coefficient.
3. The method of claim 1, wherein the plurality of temperature samples further comprises temperature samples of water entering the host and/or temperature samples of water entering the main water pipe.
4. The method of claim 3, wherein determining the likeness score based on the plurality of temperature sample data comprises:
determining a second temperature difference value based on the inlet water temperature sampling data and the outlet water temperature sampling data about the non-running host machine and the difference value between the maximum value and the minimum value in the inlet water temperature sampling data about the running host machine and/or the temperature sampling data of the water inlet main pipe;
determining whether the second temperature difference is less than a second threshold; and
in response to determining that the second temperature difference value is less than the second threshold, determining temperature sample data corresponding to the second temperature difference value as second similar temperature sample data to determine a third similar occupancy based on an occupancy of the second similar temperature sample data in the temperature sample data.
5. The method of claim 3, wherein determining the likeness score based on the plurality of temperature sample data comprises:
and determining a correlation coefficient between a plurality of temperature sampling data in the inlet water temperature sampling data about the non-running host, the outlet water temperature sampling data, the inlet water temperature sampling data about the running host and the temperature sampling data of the inlet water main pipe, so as to determine a fourth similarity ratio based on the correlation coefficient.
6. The method of claim 1, wherein determining that the similar proportion satisfies a predetermined condition comprises: determining that the similarity score satisfies at least one of:
determining that the first similar occupancy is greater than a first occupancy threshold;
determining that the second similar ratio is greater than a second ratio threshold;
determining that the third similar occupancy is greater than a third occupancy threshold; and
determining that the fourth similar occupancy is greater than a fourth occupancy threshold.
7. An electronic device, comprising:
at least one processing unit;
at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions when executed by the at least one processing unit, cause the electronic device to perform the steps of the method of any of claims 1-6.
8. A computer-readable storage medium, having stored thereon a computer program which, when executed by a machine, implements the method of any of claims 1-6.
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