A temperature control device operation control method and system, electronic device, and storage medium

Abstract

Embodiments of the present application disclose a temperature control device operation control method and system, electronic equipment and storage medium. The system comprises: a moving average value acquisition module configured to acquire a current moving average value of an operation parameter of a temperature control device in operation based on a current detection value of the operation parameter through a time window; an abnormality evaluation result acquisition module configured to determine a current abnormality detection threshold of the operation parameter based on a target abnormality value corresponding to the operation parameter and the current moving average value, and determine a current abnormality evaluation result of the operation parameter based on the current detection value and the current abnormality detection threshold; and a reporting data determination and sending module configured to determine reporting data based on the current abnormality evaluation result, and send the reporting data to an intelligent control device. Embodiments of the present application can timely and accurately acquire an abnormal operation state of a temperature control device to appropriately control the temperature control device.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of temperature control equipment, and in particular to a temperature control equipment operation control method and system, an electronic device, and a storage medium. BACKGROUND

[0002] In the prior art, manual operation and monitoring play a dominant role in the operation control of the temperature control equipment of the target building space. High proportion of manual dependence leads to a significant increase in operation and maintenance costs, and limits the response speed of the temperature control system. It is also difficult to ensure the accuracy of the operation control of the temperature control equipment. There may be a situation that the abnormal operation of the temperature control equipment cannot be found in time and accurately, which leads to the continuous deterioration of the operation state of the temperature control equipment and affects the normal operation of the temperature control system. SUMMARY

[0003] The embodiments of the present application provide a temperature control equipment operation control method and system, an electronic device, and a storage medium, which can timely and accurately obtain the abnormal operation state of the temperature control equipment to control the temperature control equipment properly.

[0004] In a first aspect, the embodiments of the present application provide a temperature control equipment operation control system, comprising: an edge computing device, which comprises:

[0005] a moving average value acquisition module configured to acquire a current moving average value of an operation parameter of a temperature control equipment in operation based on a current detection value of the operation parameter through a time window;

[0006] an abnormality evaluation result acquisition module configured to determine a current abnormality detection threshold of the operation parameter based on a target abnormality value corresponding to the operation parameter and the current moving average value, and determine a current abnormality evaluation result of the operation parameter based on the current detection value and the current abnormality detection threshold; the target abnormality value is a historical abnormality detection value of a plurality of operation parameters; and

[0007] a reporting data determination and sending module configured to determine reporting data based on the current abnormality evaluation result, and send the reporting data to an intelligent control device, so that the intelligent control device controls the temperature control equipment in operation based on the reporting data.

[0008] In a second aspect, the embodiments of the present application provide a temperature control equipment operation control method applied to an edge computing device, comprising:

[0009] acquiring a current moving average value of an operation parameter of a temperature control equipment in operation based on a current detection value of the operation parameter through a time window;

[0010] determine a current abnormality detection threshold of the operation parameter based on the target abnormality value corresponding to the operation parameter and the current moving average value, and determine a current abnormality evaluation result of the operation parameter based on the current detection value and the current abnormality detection threshold; the target abnormality value is a historical abnormality detection value of a plurality of operation parameters; and

[0011] determine reporting data based on the current abnormality evaluation result, and send the reporting data to the intelligent control device, so that the intelligent control device controls the temperature control device in operation based on the reporting data.

[0012] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the temperature control device operation control method according to any of the embodiments of the present application when executing the program.

[0013] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and the program is executable on a processor to implement the temperature control device operation control method according to any of the embodiments of the present application.

[0014] The temperature control device operation control method, system, electronic device and storage medium provided by the embodiments of the present application can reduce the manual dependence of temperature control device operation control, timely and accurately obtain abnormal parameters of the temperature control device in operation, timely and accurately discover the abnormal situation of the temperature control device, and further quickly respond, so as to avoid the continuous deterioration of the operation state of the temperature control device, and to control the temperature control device properly. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be considered as limiting the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0016] Figure 1 is a structural schematic diagram of the temperature control device operation control system provided by the embodiments of the present application;

[0017] Figure 2is another structural schematic view of the operation control system of the temperature control device provided by the embodiment of the present application;

[0018] Figure 3 is another structural schematic view of the operation control system of the temperature control device provided by the embodiment of the present application;

[0019] Figure 4 is a flow schematic view of the operation control method of the temperature control device provided by the embodiment of the present application;

[0020] Figure 5 is a structural schematic view of the electronic device provided by the embodiment of the present application; DETAILED DESCRIPTION

[0021] In order to enable personnel in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] Figure 1 is a structural view of the operation control system of the temperature control device provided by the embodiment of the present application, which comprises an edge computing device, and is suitable for executing the operation control method of the temperature control device provided by the embodiment of the present application.

[0024] As shown in Figure 1 , the edge computing device of the system can specifically include:

[0025] The moving average value acquisition module 101 is configured to acquire a current moving average value of an operation parameter of the temperature control device in operation based on a current detection value of the operation parameter by a time window. This can facilitate determining an abnormality evaluation result of the operation parameter based on the current moving average value.

[0026] Specifically, the edge computing device can include one or more edge computing nodes.

[0027] Specifically, the in-operation temperature control device can include one temperature control device or multiple temperature control devices.

[0028] Specifically, the edge computing node can correspond to one of the multiple temperature control devices, or one edge computing node can be configured for multiple in-operation temperature control devices.

[0029] Specifically, the temperature control device can include a water chiller.

[0030] Specifically, the operation parameter of the in-operation temperature control device can include one type of operation parameter or multiple types of operation parameters.

[0031] Specifically, the time window can have a fixed length or a variable length.

[0032] Specifically, the fixed length of the time window can be set based on the type of the corresponding operation parameter, or can be set according to the stability of the corresponding operation parameter.

[0033] Optionally, the process of obtaining the current moving average value of the operation parameter of the in-operation temperature control device based on the current detection value of the operation parameter through the time window includes: for each operation parameter in the multiple operation parameters, using the time window to obtain the latest data value, i.e., the current detection value, of the current operation parameter at a preset moving step, and removing the oldest data value in the time window to obtain the latest set of operation parameters of the current operation parameter; calculating the average value of the latest set of operation parameters to obtain the current moving average value of the operation parameter.

[0034] Specifically, the process of calculating the average value of the latest set of operation parameters can be based on the following formula:

[0035]

[0036] wherein, MA t represents the current moving average value, n represents the number of operation parameters; x t represents the operation parameter value corresponding to time t.

[0037] In an optional specific embodiment, as shown in Figure 2 the edge computing device further includes: a current window length obtaining module 202, configured to determine a current window length based on a current abnormal frequency of the operation parameter, the current abnormal frequency being the frequency of the operation parameter being abnormal within a second preset time length.

[0038] Specifically, the frequency of the abnormality of the operation parameter can be represented by a probability of the operation parameter being abnormal in a unit time period, or represented by a probability of the operation parameter being abnormal when the operation parameter is collected in each time window.

[0039] In an optional embodiment, the moving average obtaining module 101 can be specifically configured to obtain the current detection value and the current moving average of the operation parameter by a time window with a length of a current window length.

[0040] Specifically, the window length corresponding to the first preset time period can be the same window length or multiple window lengths.

[0041] Specifically, the second preset time period can be set based on experience, for example, the second preset time period can be set to one day.

[0042] Specifically, an initial value can be set for the window length to obtain an initial time window, for example, the window length of the initial time window can be set to 5 minutes; when the first operation parameter and the corresponding moving average are obtained, the initial time window can be used for obtaining; then the frequency of the operation parameter being abnormal when the moving average is obtained based on the initial time window is obtained, and the window length of the next time window is determined based on the frequency.

[0043] In an optional embodiment, the edge computing device as shown in Figure 2 Further includes a reference abnormal frequency determining module 201 configured to determine a reference abnormal frequency of the operation parameter based on a frequency of the operation parameter being abnormal in a historical third preset time period.

[0044] Specifically, the historical third preset time period can be preferably a historical time period in which no abnormal misjudgment or omission occurs, or a historical time period in which the number of abnormal misjudgments or omissions is less than a threshold. Specifically, the third preset time period can be set based on experience, for example, the third preset time period can be 6 months.

[0045] In an optional embodiment, the process of determining the current window length based on the current abnormal frequency of the operation parameter includes: determining the current window length of the operation parameter based on the current abnormal frequency of the operation parameter and the reference abnormal frequency.

[0046] Optionally, when the current abnormal frequency is greater than the reference frequency, the current window length is set to a smaller value; when the abnormal frequency is less than the reference frequency, the current window length is set to a larger value.

[0047] Optionally, the process of determining the current window length of the operation parameter based on the current abnormal frequency of the operation parameter and the reference abnormal frequency includes: determining the current window length based on the current abnormal frequency, the reference abnormal frequency, and a previous time window length.

[0048] Specifically, the current window length can be determined based on the following formula:

[0049] n t =n t-1 +sgn(f 参考 -f 异常 )×Δn

[0050] wherein n t represents the current window length; n t-1 represents the previous window length; f 参考 represents the reference abnormal frequency; f 异常 represents the current abnormal frequency; Δn is a window adjustment step, which is a preset constant; sgn is a sign function, which is positive if f 参考 >f 异常 , and negative if f 参考 <f 异常 .

[0051] Specifically, by dynamically adjusting the time window length for obtaining the corresponding moving average of the running parameter, the frequency of obtaining the corresponding moving average of the running parameter can be adjusted based on the frequency of the abnormal value of the running parameter, i.e., the size of the data fluctuation of the running parameter, and the frequency of detecting the abnormality of the running parameter is further adjusted, so as to facilitate detecting whether the running parameter is abnormal at a lower frequency when the data is relatively stable, saving computing resources and storage resources, and increasing the frequency of abnormality detection when the data fluctuates greatly, ensuring that no abnormal parameters are missed, reducing false positives and omissions, and further accurately controlling the operation of the temperature control device.

[0052] The abnormality evaluation result obtaining module 102 is configured to determine a current abnormality detection threshold of the running parameter based on the target abnormal value and the current moving average value of the running parameter, and determine a current abnormality evaluation result of the running parameter based on the current detection value and the current abnormality detection threshold. The target abnormal value is a historical abnormality detection value of the plurality of running parameters. By adaptively and dynamically adjusting the abnormality detection threshold, the change of the running parameter can be better adapted to improve the accuracy of abnormality detection.

[0053] Specifically, during the operation of the device, as the environment and mechanical state change, the normal range of the running parameter also changes, and therefore the threshold of the running parameter needs to be dynamically adjusted to adapt to the change of the corresponding environment and mechanical state.

[0054] Specifically, the historical first preset time length can be preferably a historical time length in which the frequency of the abnormal value of the moving average of the running parameter is relatively high. Specifically, the first preset time length can be set based on experience, for example, the first preset time length can be 6 months.

[0055] Optionally, the process of determining the current anomaly detection threshold of the operation parameter based on the target anomaly value corresponding to the operation parameter and the current moving average value comprises: calculating the current anomaly detection threshold based on the difference between each target anomaly value and the current moving average value and the current moving average value.

[0056] Optionally, the process of calculating the current anomaly detection threshold based on the difference between each target anomaly value and the current moving average value and the current moving average value comprises:

[0057] The difference between each target anomaly value and the current moving average value is obtained to obtain a plurality of target difference values; the standard deviation of the plurality of target difference values is calculated; and the sum and / or difference of the current moving average value and the standard deviation is calculated to obtain the current anomaly detection threshold.

[0058] The reporting data determination and sending module 103 is configured to determine reporting data based on the current anomaly evaluation result, and send the reporting data to the intelligent control device, so that the intelligent control device controls the temperature control device in operation based on the reporting data. In this way, the intelligent control device can reduce the dependence on manual operation, and timely and accurately obtain the abnormal parameters of the temperature control device in operation, so as to timely and accurately discover the abnormal operation of the temperature control device, and further quickly respond to avoid the continuous deterioration of the operation state of the temperature control device.

[0059] Optionally, the process of determining the current anomaly evaluation result of the operation parameter based on the current detection value and the current anomaly detection threshold comprises:

[0060] The current anomaly evaluation result is determined based on whether the current detection value deviates from the normal detection value range determined based on the current anomaly detection threshold, the deviation degree of the current detection value from the normal detection value range determined based on the current anomaly detection threshold, and / or the abnormal duration corresponding to the current detection value.

[0061] Specifically, the deviation degree of the current detection value can be determined based on the difference between the current detection value and the current anomaly detection threshold.

[0062] Specifically, the abnormal duration corresponding to the current detection value can be understood as the duration of the continuously occurring abnormal detection values with the current detection value when the current detection value is an abnormal value.

[0063] Specifically, the abnormal evaluation result can also be determined according to the number of continuously occurring abnormal detection values with the current detection value when the current detection value is an abnormal value.

[0064] Specifically, when the current detection value of one operation parameter is abnormal, the current anomaly evaluation result can be determined according to whether the current detection value of other operation parameters is abnormal and the like.

[0065] Optionally, the current abnormality evaluation result includes: slight abnormality, moderate abnormality and severe abnormality.

[0066] Optionally, the process of determining the reporting data based on the current abnormality evaluation result includes: adding the current abnormality evaluation result to the reporting data when the current abnormality evaluation result is moderate abnormality and / or severe abnormality. In this way, the intelligent control device can not process slight abnormality data which has no or small influence on the normal and safe operation of the temperature control device, and can process moderate abnormality and severe abnormality data which have influence on the normal and safe operation of the temperature control device in time, and control the temperature control device appropriately, for example, reduce the operation load.

[0067] Optionally, the edge computing device provided by the embodiment of the present application further includes: a control command forwarding module, configured to receive the control command of the temperature control device sent by the intelligent control device, and forward the control command to the temperature control device.

[0068] The temperature control device operation control system provided by another embodiment of the present application is further introduced as follows,

[0069] In the embodiment of the present application, the temperature control device includes each temperature control device of the target building space, and the temperature control device operation control system can further include an intelligent control device.

[0070] Optionally, as shown in Figure 3 The intelligent control device includes:

[0071] The prediction temperature control energy consumption obtaining module 301 is configured to predict the change value of the temperature control energy consumption of the target building space within a first preset time length in the future based on the temperature control energy consumption related factors of the target building space, to obtain prediction temperature control energy consumption change data. This can facilitate determining the target refrigeration amount change data based on the temperature control energy consumption change data.

[0072] Specifically, the temperature control energy consumption of the target building space can be understood as the electric energy consumed by the temperature control device for temperature control of the target building space.

[0073] Specifically, the temperature control energy consumption related factors of the target building space include: temperature, humidity, human flow density and structure space information inside the target building space.

[0074] Specifically, the temperature control energy consumption related factors of the target building space can further include: historical temperature control energy consumption of the target building space, external meteorological data and external event information, etc. Specifically, the external event can be, for example, whether there is a special personnel gathering activity, etc.

[0075] Specifically, the temperature control energy consumption related factors of the target building space can further include: holiday information.

[0076] Optionally, the process of predicting the predicted temperature control energy consumption change data based on the target building space temperature control energy consumption related factor and predicting the target building space temperature control energy consumption change value over time within the first preset time period in the future includes:

[0077] The target building space temperature control energy consumption related factor is predicted by a neural network model, such as a long short-term memory network model, to obtain the predicted temperature control energy consumption change data.

[0078] Optionally, the above step 302 can be triggered based on a preset period. For example, the above step 302 can be triggered once an hour.

[0079] Optionally, the above first preset time period can be set according to the use scenario of the target building space. For example, for a commercial comprehensive target building space with a 24-hour cycle change in use, the first preset time period can be set to 24 hours.

[0080] Specifically, when the target building space has a large change in the number of people, such as a subway station, the first preset time period can be set to a small value, for example, it can be set to 2 hours.

[0081] Optionally, the predicted temperature control energy consumption acquisition module predicts the energy consumption change data every 10 minutes within the next 24 hours based on the real-time acquired temperature control energy consumption related factor to obtain the predicted temperature control energy consumption change data.

[0082] The target refrigeration capacity acquisition module 302 is configured to determine the target refrigeration capacity change value of each temperature control device of the target building space over time within the first preset time period based on the predicted temperature control energy consumption change data to obtain the target refrigeration capacity change data.

[0083] In an optional specific example, on a typical summer weekday, at 2 a.m., it is determined according to the predicted temperature control energy consumption change data that there will be a power consumption peak at 3 p.m. today. In order to avoid the risk of exceeding the contract capacity and save electricity costs, a plan is made to control the operation of the temperature control device to store refrigeration capacity during the low electricity price period and reduce the refrigeration capacity during the power consumption peak period, thereby obtaining the target refrigeration capacity change data.

[0084] In an optional specific example, the predicted temperature control energy consumption change data is adjusted by reducing the peak value and increasing the valley value.

[0085] The control module 303 is configured to control the operation of the temperature control device based on the target refrigeration capacity change data and the reporting data sent by the edge computing device.

[0086] Optionally, the process of controlling the operation of the temperature control device based on the target refrigeration capacity change data and the reporting data sent by the edge computing device includes:

[0087] The temperature control device control instruction is generated based on the target refrigeration capacity change data and the reported data, and is sent to the corresponding temperature control device through the edge computing device to control the corresponding temperature control device.

[0088] Optionally, the process of controlling the running temperature control device based on the target refrigeration capacity change data comprises determining the optimal running load of the running temperature control device based on the target refrigeration capacity and the target energy efficiency ratio at the current target time.

[0089] Optionally, the process of determining the optimal running load of the running temperature control device based on the target refrigeration capacity and the target energy efficiency ratio at the current target time comprises determining the input power of the running temperature control device based on the following formula:

[0090]

[0091] wherein COP represents the target energy efficiency ratio, Q represents the target refrigeration capacity at the current time, and P represents the current input power.

[0092] Then, the optimal running load of the running temperature control device is determined based on the input power of the running temperature control device.

[0093] Specifically, the target energy efficiency ratio can be obtained from the device parameters of the running temperature control device.

[0094] Specifically, by determining the optimal running load of the running temperature control device based on the target energy efficiency ratio, it is possible to ensure that the cold capacity demand is met while optimizing energy consumption and prolonging the service life of the device.

[0095] Optionally, when the abnormal evaluation result data of the running parameter is not included in the reported data, the running temperature control device is controlled based on the target refrigeration capacity change data, so that the total running load of the running temperature control device is consistent with the target refrigeration capacity change data.

[0096] Optionally, the number of running temperature control devices is multiple.

[0097] Optionally, the process of controlling the running temperature control device based on the target refrigeration capacity change data and the reported data sent by the edge computing device comprises:

[0098] determining whether to change the number of running temperature control devices based on the target refrigeration capacity change data; determining the optimal running load of the running temperature control device based on the reported data; and regulating the running state of the running temperature control device based on the optimal running load.

[0099] Specifically, when the temperature control energy consumption value in the fourth preset time period predicted at the current time is less than the temperature control energy consumption value in the fourth preset time period predicted at the last time, the target refrigerating capacity is reduced, and the number of the temperature control devices in operation can be reduced accordingly; when the temperature control energy consumption value in the fourth preset time period predicted at the current time is greater than the temperature control energy consumption value in the fourth preset time period predicted at the last time, the target refrigerating capacity is increased, and the number of the temperature control devices in operation can be increased accordingly.

[0100] In an optional specific example, at 12:00 noon, it is predicted that the power consumption peak at 3:00 pm is higher than expected, and the target refrigerating capacity is also increased accordingly, so that one cold water unit is added in operation.

[0101] Specifically, the fourth preset time period is less than the first prediction time period.

[0102] Optionally, the edge computing device, as shown in Figure 2 The edge computing device further comprises an operation parameter acquisition and preprocessing module configured to acquire and preprocess the original detection value of the operation parameter at the current time to obtain a current detection value; and a reporting data determination and sending module configured to add the current detection value to the reporting data.

[0103] Specifically, the preprocessing of the original detection value of the operation parameter comprises denoising processing of the original operation parameter.

[0104] Optionally, the operation parameter comprises the current detection value of the vibration state parameter, the temperature state parameter and the pressure state parameter of the temperature control device in operation.

[0105] Optionally, the optimal operation load of the temperature control device in operation is determined based on the reporting data, comprising:

[0106] calculating a current health index of the temperature control device in operation based on the current detection value of the vibration state parameter, the temperature state parameter and the pressure state parameter; and determining the optimal operation load of the temperature control device in operation based on the current health index.

[0107] Specifically, the calculation of the current health index of the temperature control device in operation based on the current detection value of the vibration state parameter, the temperature state parameter and the pressure state parameter can be performed based on the following formula:

[0108] HI = w1·T + w2·V + w3·P

[0109] wherein HI represents the current health index of the device; w1, w2 and w3 are weights of different parameters, which can be determined in advance through experiments; T, V and P represent the temperature state parameter, the vibration state parameter and the pressure state parameter respectively.

[0110] Optionally, when the current health index exceeds a normal current health index of the corresponding device, and a maintenance or adjustment operation is triggered, the optimal operation load of the corresponding device is set to a smaller value or 0, so as to reduce the operation load or stop the maintenance, thereby avoiding continuous deterioration of the rated health state of the temperature control device and affecting the normal operation of the temperature control system.

[0111] Optionally, the reported data comprises a current abnormality evaluation result of the temperature control device in operation.

[0112] Optionally, the optimal operation load of the temperature control device in operation is determined based on the reported data, comprising: determining the optimal operation load of the temperature control device in operation based on the corresponding current abnormality evaluation result.

[0113] Specifically, when the current abnormality evaluation result is a serious abnormality, the optimal operation load of the corresponding device is set to a smaller value or 0, so as to reduce the operation load or stop the maintenance, thereby avoiding continuous deterioration of the rated health state of the temperature control device and affecting the normal operation of the temperature control system.

[0114] Figure 4 A flowchart of a temperature control device operation control method provided by an embodiment of the present application is provided. The embodiment can be applied to a scenario of operation control of a temperature control device of a target building space. The method can be executed by an edge computing device in a temperature control device operation control system provided by an embodiment of the present application. The device can be implemented in a software and / or hardware manner. In a specific embodiment, the device can be integrated in an electronic device, such as a computer, a server, etc. The following embodiments will be described by taking the device integrated in the electronic device as an example. Referring to Figure 4 The method can specifically include the following steps:

[0115] In step 401, a current moving average value of an operation parameter of a temperature control device in operation is obtained based on a current detection value of the operation parameter through a time window. This step can facilitate determination of an abnormality evaluation result of the operation parameter based on the current moving average value.

[0116] Optionally, before step 401, an original detection value of the operation parameter at a current time is collected and preprocessed to obtain the current detection value.

[0117] Optionally, before step 401, a current window length is determined based on a current abnormality frequency of the operation parameter. The current abnormality frequency is a frequency of occurrence of an abnormality of the operation parameter within a second preset time length.

[0118] Optionally, the process of obtaining the current moving average value of the operation parameter based on the current detected value of the operation parameter of the operating temperature control device through the time window with the current window length comprises: obtaining the current detected value and the current moving average value of the operation parameter through the time window with the current window length.

[0119] Optionally, before the process of obtaining the current detected value and the current moving average value of the operation parameter through the time window with the current window length, a reference abnormal frequency of the operation parameter is determined based on a frequency of occurrence of an abnormality of the operation parameter in a historical third preset time length; and the process of determining the current window length based on the current abnormal frequency of the operation parameter comprises: determining the current window length of the operation parameter based on the current abnormal frequency and the reference abnormal frequency of the operation parameter.

[0120] In step 402, a current abnormal detection threshold of the operation parameter is determined based on a target abnormal value corresponding to the operation parameter and the current moving average value, and a current abnormal evaluation result of the operation parameter is determined based on the current detected value and the current abnormal detection threshold; the target abnormal value is a historical abnormal detection value of the plurality of operation parameters; the abnormal detection threshold is adaptively and dynamically adjusted in this step, which can better adapt to the change of the operation parameter to improve the accuracy of abnormal detection.

[0121] Optionally, the process of determining the current abnormal detection threshold of the operation parameter based on the target abnormal value corresponding to the operation parameter and the current moving average value comprises: calculating the current abnormal detection threshold based on a difference between each target abnormal value and the current moving average value, and the current moving average value.

[0122] In step 403, reported data is determined based on the current abnormal evaluation result, and the reported data is sent to the intelligent control device, so that the intelligent control device controls the operating temperature control device based on the reported data; based on the steps 401-402, the abnormal parameters of the operating temperature control device can be timely and accurately obtained on the basis of reducing the dependence on manual operation, and the operating abnormal condition of the temperature control device can be timely and accurately found, and further rapid response can be made to avoid continuous deterioration of the operating state of the temperature control device.

[0123] Optionally, the process of determining the current abnormal evaluation result of the operation parameter based on the current detected value and the current abnormal detection threshold comprises:

[0124] The current abnormal evaluation result is determined based on whether the current detected value deviates from a normal detected value range determined based on the current abnormal detection threshold, a deviation degree of the current detected value from the normal detected value range determined based on the current abnormal detection threshold, and / or an abnormal duration corresponding to the current detected value.

[0125] Optionally, the current abnormality evaluation result includes slight abnormality, moderate abnormality and severe abnormality. The process of determining the reporting data based on the current abnormality evaluation result includes: adding the current abnormality evaluation result to the reporting data when the current abnormality evaluation result is moderate abnormality and / or severe abnormality.

[0126] Optionally, the process of determining the reporting data based on the current abnormality evaluation result includes: determining the current detection value and the current abnormality evaluation result as the content of the reporting data.

[0127] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional modules is exemplified, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the above described functional modules can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0128] The embodiment of the present application also provides an electronic device, including a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the program to realize the temperature control device running control method provided by any of the above embodiments.

[0129] The embodiment of the present application also provides a computer readable medium, which stores a computer program, and the program is executed by a processor to realize the temperature control device running control method provided by any of the above embodiments.

[0130] The embodiment of the present application also provides a computer program product, including a computer program, and the computer program is executed by a processor to realize the temperature control device running control method as any of the embodiments of the present application.

[0131] The following refers to Figure 5 which shows the structural schematic diagram of a computer system 500 suitable for realizing the electronic device of the embodiment of the present application. Figure 5 The electronic device shown is only an example, and should not bring any limitation to the function and use range of the embodiment of the present application.

[0132] As Figure 5As shown, the computer system 500 includes a central processing unit (CPU) 501 which can perform various appropriate actions and processes in accordance with programs stored in a read only memory (ROM) 502 or loaded from a storage section 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the system 500 are also stored. The CPU 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0133] Connected to the I / O interface 505 are an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as necessary. A removable recording medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 510 as necessary, so that a computer program read therefrom is installed into the storage section 508 as necessary.

[0134] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program in accordance with the embodiments disclosed herein. For example, the embodiments disclosed herein include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 509 and / or installed from the removable recording medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-described functions defined in the system of the present application are performed.

[0135] It should be noted that the computer-readable medium shown in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to, an electrical connection having one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component. In the present application, the computer-readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, which can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or component. The program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0136] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code containing one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different order than that shown in the drawings. For example, two blocks that are shown in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0137] The modules and / or units described in the embodiments of the present application can be implemented by software, or can be implemented by hardware. The described modules and / or units can also be arranged in a processor, for example, can be described as: a processor includes a moving average value obtaining module, an abnormality evaluation result obtaining module, and a reporting data determining and sending module. Among them, the names of these modules do not constitute a limitation of the modules themselves in some cases.

[0138] As another aspect, the present application also provides a computer readable medium, which can be included in the device described in the above embodiments, or can exist independently without being assembled into the device. The computer readable medium carries one or more programs, when the one or more programs are executed by the device, the device is caused to implement: obtaining a current moving average value of an operating parameter of a running temperature control device based on a current detection value of the operating parameter in a time window; determining a current abnormality detection threshold of the operating parameter based on a target abnormality value corresponding to the operating parameter and the current moving average value, and determining a current abnormality evaluation result of the operating parameter based on the current detection value and the current abnormality detection threshold; the target abnormality value is a historical abnormality detection value of a plurality of operating parameters; and

[0139] determining reporting data based on the current abnormality evaluation result, and sending the reporting data to an intelligent control device, so that the intelligent control device controls the running temperature control device based on the reporting data.

[0140] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can occur depending on design requirements and other factors. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A temperature-controlled equipment operation control system comprising an edge computing device, characterized in that, The edge computing device comprises: a moving average value acquisition module configured to acquire a current moving average value of an operating parameter of a temperature control device in operation based on a current detection value of the operating parameter within a time window; an abnormality evaluation result acquisition module configured to determine a current abnormality detection threshold of the operating parameter based on a target abnormality value corresponding to the operating parameter and the current moving average value, and determine a current abnormality evaluation result of the operating parameter based on the current detection value and the current abnormality detection threshold; the target abnormality value is a historical abnormality detection value of a plurality of operating parameters; and a reporting data determination and sending module configured to determine reporting data based on the current abnormality evaluation result, and send the reporting data to an intelligent control device, so that the intelligent control device controls the temperature control device in operation based on the reporting data; The edge computing device further comprises: a reference abnormality frequency determination module configured to determine a reference abnormality frequency of the operating parameter based on a frequency of occurrence of abnormality of the operating parameter within a historical third preset time period; a current window length acquisition module configured to determine the current window length of the operating parameter based on a current abnormality frequency of the operating parameter and the reference abnormality frequency; the current abnormality frequency is a frequency of occurrence of abnormality of the operating parameter within a second preset time period; The moving average value acquisition module is specifically configured to acquire the current detection value and the current moving average value of the operating parameter through a time window with a length of the current window length.

2. The temperature control apparatus operation control system according to claim 1, characterized by, Further comprising: an intelligent control device, the temperature control device comprising temperature control devices of a target building space, the intelligent control device comprising: a predicted temperature control energy consumption acquisition module configured to predict a temperature control energy consumption of the target building space within a future first preset time period based on a temperature control energy consumption related factor of the target building space to obtain predicted temperature control energy consumption change data; a target refrigeration capacity acquisition module configured to determine a change value of a target refrigeration capacity of the temperature control devices of the target building space over time within the first preset time period based on the predicted temperature control energy consumption change data to obtain target refrigeration capacity change data; and a control module configured to control the temperature control device in operation based on the target refrigeration capacity change data and the reporting data sent by the edge computing device.

3. The temperature-controlled equipment operation control system of claim 1, wherein, The determination of the current abnormality detection threshold of the operating parameter based on the target abnormality value corresponding to the operating parameter and the current moving average value comprises: calculating the current abnormality detection threshold based on a difference between each target abnormality value and the current moving average value, and the current moving average value.

4. The temperature control device operation control system according to claim 1, wherein The determination of the current abnormality evaluation result of the operating parameter based on the current detection value and the current abnormality detection threshold comprises: The current abnormality evaluation result is determined based on whether the current detection value deviates from a normal detection value range determined based on the current abnormality detection threshold, a deviation degree of the current detection value from the normal detection value range determined based on the current abnormality detection threshold, and / or an abnormality duration corresponding to the current detection value.

5. The temperature control device operation control system of claim 1, wherein The current abnormality evaluation result includes slight abnormality, moderate abnormality, and severe abnormality. The reporting data is determined based on the current abnormality evaluation result, including: When the current abnormality evaluation result is moderate abnormality and / or severe abnormality, the current abnormality evaluation result is added to the reporting data.

6. The temperature-controlled equipment operation control system of claim 2, wherein, The operation in the temperature control device is controlled based on the target refrigeration capacity change data and the reporting data sent by the edge computing device, including: It is determined whether to change the number of operation in the temperature control device based on the target refrigeration capacity change data; The optimal operation load of the operation in the temperature control device is determined based on the reporting data; and The operation state of the operation in the temperature control device is regulated based on the optimal operation load.

7. The temperature control device operation control system of claim 2, wherein The operation in the temperature control device is controlled based on the target refrigeration capacity change data, including: The optimal operation load of the operation in the temperature control device is determined based on the target refrigeration capacity and the target energy efficiency ratio of the current target time.

8. The temperature-controlled equipment operation control system of claim 1, wherein, The edge computing device further includes: An operation parameter acquisition and preprocessing module for acquiring and preprocessing the original detection value of the operation parameter at the current time to obtain the current detection value; The reporting data determination and sending module is further configured to add the current detection value to the reporting data.

9. The temperature-controlled equipment operation control system of claim 8, wherein, The operation parameter includes the current detection value of the vibration state parameter, the temperature state parameter, and the pressure state parameter of the operation in the temperature control device; The optimal operation load of the operation in the temperature control device is determined based on the reporting data, including: The current health index of the operation in the temperature control device is calculated based on the current detection value of the vibration state parameter, the temperature state parameter, and the pressure state parameter; and The optimal operation load of the operation in the temperature control device is determined based on the current health index. The reporting data includes the current abnormality evaluation result of the operation in the temperature control device; 10. The temperature-controlled equipment operation control system of claim 6, wherein, The optimal operation load of the operation in the temperature control device is determined based on the reporting data, including: The optimal operation load of the operation in the temperature control device is determined based on the corresponding current abnormality evaluation result. including:

11. A method for controlling the operation of a temperature control device, applied to an edge computing device in a temperature control device operation control system, characterized in that, The current moving average value of the operation parameter is obtained based on the current detection value of the operation parameter of the operation in the temperature control device through a time window; The current abnormality evaluation result of the operation parameter is determined based on the target abnormality value corresponding to the operation parameter and the current moving average value, and the current abnormality evaluation result of the operation parameter is determined based on the current detection value and the current abnormality detection threshold; The target abnormality value is a historical abnormality detection value of a plurality of operation parameters; and ​ ​ Determine reporting data based on the current abnormality evaluation result, and send the reporting data to an intelligent control device, so that the intelligent control device controls the operating temperature control device based on the reporting data; Before the current moving average value of the operating parameter of the operating temperature control device is obtained based on the current detection value of the operating parameter within the time window, the method further comprises: Determine a reference abnormality frequency of the operating parameter based on a frequency of abnormality of the operating parameter within a third preset time period in history; Determine the current window length of the operating parameter based on the current abnormality frequency and the reference abnormality frequency of the operating parameter; the current abnormality frequency is a frequency of abnormality of the operating parameter within a second preset time period; The current moving average value of the operating parameter of the operating temperature control device is obtained based on the current detection value of the operating parameter within the time window, comprising: obtaining the current detection value and the current moving average value of the operating parameter within a time window with a length of the current window length.

12. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the temperature control device operation control method in claim 11.

13. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the temperature control device operation control method in claim 11.

Images