Temperature control equipment operation control method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a temperature control equipment operation control method and system, electronic equipment and a storage medium, and the system comprises a moving average value obtaining module which is used for obtaining a current moving average value of an operation parameter based on a current detection value of the operation parameter of the temperature control equipment in operation through a time window; the abnormity evaluation result acquisition module is used for determining a current abnormity detection threshold value of the operation parameter based on a target abnormity value corresponding to the operation parameter and the current moving average value, and determining a current abnormity evaluation result of the operation parameter based on a current detection value and the current abnormity detection threshold value; and the reported data determining and sending module is used for determining reported data based on the current abnormity evaluation result and sending the reported data to the intelligent control device. According to the embodiment of the invention, the abnormal operation state of the temperature control equipment can be timely and accurately acquired so as to properly control the temperature control equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control equipment, and in particular to a temperature control equipment operation control method, system, electronic equipment and storage medium. Background Art

[0002] In the prior art, manual operation and monitoring play a dominant role in the operation and control of temperature control equipment in the target building space. The high proportion of manual dependence leads to a significant increase in operation and maintenance costs. The high proportion of manual dependence also limits the response speed of the temperature control system, and it is difficult to ensure the accuracy of the operation and control of the temperature control equipment. There may be situations where abnormal operation of the temperature control equipment cannot be discovered in a timely and accurate manner, resulting in continuous deterioration of the operating status of the temperature control equipment and affecting the normal operation of the temperature control system. Summary of the invention

[0003] Embodiments of the present invention provide a temperature control device operation control method, system, electronic device and storage medium, which can timely and accurately obtain the abnormal operation status of the temperature control device to properly control the temperature control device.

[0004] In a first aspect, an embodiment of the present invention provides a temperature control device operation control system, including: an edge computing device, wherein the edge computing device includes:

[0005] A moving average value acquisition module, used to acquire the current moving average value of the operating parameter based on the current detection value of the operating parameter of the operating temperature control device through a time window;

[0006] an abnormality assessment 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 assessment 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 the operating parameters; and

[0007] The reporting data determination and sending module is used to determine the reporting data based on the current abnormality assessment result, and send the reporting data to the intelligent control device, so that the intelligent control device controls the running temperature control device based on the reporting data.

[0008] In a second aspect, an embodiment of the present invention provides a temperature control device operation control method, which is applied to an edge computing device, including:

[0009] Obtaining a current moving average value of the operating parameter based on a current detection value of the operating parameter of the operating temperature control device through a time window;

[0010] 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 assessment 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 the operating parameters; and

[0011] Reporting data is determined based on the current abnormality assessment result, and the reporting data is sent to the intelligent control device, so that the intelligent control device controls the running temperature control device based on the reporting data.

[0012] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a temperature control device operation control method as described in any one of the embodiments of the present invention is implemented.

[0013] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a temperature control device operation control method as described in any one of the embodiments of the present invention.

[0014] The temperature control device operation control method, system, electronic device and storage medium provided by the embodiments of the present invention, obtain the current moving average value corresponding to the temperature control device in operation by setting an edge computing device, and determine the abnormal evaluation result of the corresponding operating parameter based on the moving average value threshold determined by the fact, and then send the reported data determined according to the abnormal evaluation result to the intelligent control device. The intelligent control device controls the operating state of the temperature control device in operation based on the reported data, which can reduce the manual dependence on the operation control of the temperature control device, timely and accurately obtain the abnormal parameters of the temperature control device in operation, and then timely and accurately discover the abnormal operation of the temperature control device, and further respond quickly, so as to avoid the continuous deterioration of the operating state of the temperature control device and properly control the temperature control device. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a structural schematic diagram of a temperature control device operation control system provided by an embodiment of the present invention;

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

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

[0019] Figure 4 It is a flow chart of a method for controlling the operation of a temperature control device provided by an embodiment of the present invention;

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

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

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

[0023] Figure 1 It is a structural diagram of the temperature control equipment operation control system provided in an embodiment of the present invention. The system includes an edge computing device, which is suitable for executing the temperature control equipment operation control method provided in an embodiment of the present invention.

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

[0025] The moving average value acquisition module 101 is used to acquire the current moving average value of the operating parameter based on the current detection value of the operating parameter of the operating temperature control device through the time window, which can be helpful to determine the abnormal evaluation result of the operating parameter based on the current moving average value.

[0026] Specifically, the above-mentioned edge computing device may include one or more edge computing nodes.

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

[0028] Specifically, the edge computing nodes may correspond one-to-one to the multiple temperature control devices, or one edge computing node may be set for multiple temperature control devices in operation.

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

[0030] Specifically, the operating parameters of the temperature control device in operation may include multiple operating parameters of one category or multiple operating parameters of multiple categories.

[0031] Specifically, the length of the time window may be a fixed window length or a variable window length.

[0032] Specifically, the fixed window length of the above time window may be set based on the category of the corresponding operating parameter, and may also be set based on the stability of the corresponding operating parameter.

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

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

[0035]

[0036] Among them, MA t represents the current moving average, n represents the number of running parameters; x t Indicates the operating parameter value corresponding to time t.

[0037] In an optional specific embodiment, if Figure 2 The edge computing device shown above also includes: a current window length acquisition module 202, which is used to determine the current window length based on the current abnormal frequency of the operating parameters, and the current abnormal frequency is the frequency of abnormal operating parameters within the previous second preset time length.

[0038] Specifically, the frequency of the abnormality of the above operating parameters can be expressed by the probability of the abnormality of the operating parameters within a unit time, or by the probability of the operating parameters appearing each time the operating parameters are collected in the time window.

[0039] In an optional specific embodiment, the moving average value acquisition module 101 can be specifically used to acquire the current detection value and the current moving average value of the operating parameter through a time window with a length equal to the current window length.

[0040] Specifically, the window length corresponding to the second preset time length may be the same window length or multiple window lengths.

[0041] Specifically, the second preset time period may be set based on experience, for example, the second preset time period may 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 obtaining the first operating parameter and the corresponding moving average value, they can be obtained based on the above initial time window. Then, the frequency of abnormal operating parameters when obtaining the moving average value 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 specific embodiment, the edge computing device is as follows: Figure 2 As shown, it also includes: a reference abnormal frequency determination module 201, which is used to determine the reference abnormal frequency of the operating parameter based on the frequency of abnormal operation of the operating parameter within a third preset time period in history.

[0044] Specifically, the third preset time period can be preferably a historical time period in which no abnormal misjudgment or missed judgment has occurred, or a historical time period in which the number of abnormal misjudgments or missed judgments has been reached. 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 specific embodiment, the process of determining the current window length based on the current abnormal frequency of the operating parameter includes: determining the current window length of the operating parameter based on the current abnormal frequency of the operating parameter and a 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 operating parameter based on the current abnormal frequency and the reference abnormal frequency of the operating parameter includes: determining the current window length based on the current abnormal frequency, the reference abnormal frequency and the 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] Among them, n t Indicates the current window length; n t-1 Indicates the previous window length; f 参考 Indicates the reference abnormal frequency; f 异常 Indicates the current abnormal frequency; Δn window adjustment step is a preset constant; sgn is the sign function, if f 参考 >f 异常 , then sgn is positive, if f 参考 <f 异常 , then sgn is negative.

[0051] Specifically, the embodiments of the present invention dynamically adjust the time window length for obtaining the corresponding moving average value of the operating parameters, and can adjust the frequency of obtaining the corresponding moving average value of the operating parameters based on the frequency of abnormal operating parameter values, that is, the size of the data fluctuation of the operating parameters, and then adjust the frequency of detecting abnormal operating parameters, so as to facilitate detecting whether the operating parameters are 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 to ensure that abnormal parameters are not missed, reduce false alarms and missed reports, and thus accurately control the operation of the temperature control equipment.

[0052] The abnormal evaluation result acquisition module 102 is used to determine the current abnormal detection threshold of the operating parameter based on the target abnormal value corresponding to the operating parameter and the current moving average value, and determine the current abnormal evaluation result of the operating parameter based on the current detection value and the current abnormal detection threshold value; the target abnormal value is the historical abnormal detection value of multiple operating parameters. By adaptively and dynamically adjusting the abnormal detection threshold, it can better adapt to the changes in the operating parameters to improve the accuracy of abnormal detection.

[0053] Specifically, during the operation of the equipment, as the environment and mechanical state change, the normal range of the operating parameters will also change, so the threshold for determining the operating parameters needs to be dynamically adjusted to adapt to the changes in the corresponding environment and mechanical state.

[0054] Specifically, the first historical preset time period may preferably be a historical time period during which the moving average abnormal value of the operating parameter has a high frequency of occurrence. Specifically, the first preset time period may be set based on experience, for example, the first preset time period may be 6 months.

[0055] Optionally, the above process of determining the current anomaly detection threshold of the operating parameter based on the target anomaly value corresponding to the operating parameter and the current moving average value includes: 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, includes:

[0057] Obtain the difference between each target abnormal value and the current moving average value to obtain multiple target difference values; calculate the standard deviation of the multiple target difference values; and calculate the sum and / or difference of the above current moving average value and the standard deviation to obtain the above current abnormality detection threshold.

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

[0059] Optionally, the process of determining the current abnormality assessment result of the operating parameter based on the current detection value and the current abnormality detection threshold includes:

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

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

[0062] Specifically, the abnormal duration corresponding to the current detection value may be understood as the duration of the abnormal detection value that appears continuously with the current detection value when the current detection value is an abnormal value.

[0063] Specifically, when the current detection value is an abnormal value, the abnormality assessment result may be determined according to the number of abnormal detection values ​​that appear continuously with the current detection value.

[0064] Specifically, when the current detection value of an operating parameter is abnormal, the current abnormality assessment result may be determined based on information such as whether the current detection values ​​of other operating parameters are abnormal.

[0065] Optionally, the above current abnormality assessment results include: slight abnormality, moderate abnormality and severe abnormality.

[0066] Optionally, the process of determining the reported data based on the current abnormality assessment result includes: when the current abnormality assessment result is a moderate abnormality and / or a severe abnormality, the current abnormality assessment result is added to the reported data. In this way, the intelligent control device does not need to process the mild abnormality data that has no or little impact on the normal and safe operation of the temperature control device, and can promptly process the moderate and severe abnormality data that has an impact or a large impact on the normal and safe operation of the temperature control device, and appropriately control the temperature control device, for example, reducing the operating load.

[0067] Optionally, the edge computing device provided by the embodiment of the present invention also includes: a control command forwarding module, which is used to receive the control command of the temperature control device sent by the intelligent control device and transmit it to the temperature control device.

[0068] The following further describes a temperature control device operation control system provided by another embodiment of the present invention.

[0069] In the embodiment of the present invention, the temperature control device includes various temperature control devices of the target building space, and the temperature control device operation control system may further include an intelligent control device.

[0070] Optional, such as Figure 3 As shown, the above-mentioned intelligent control device includes:

[0071] The predicted temperature control energy consumption acquisition module 301 is used to predict the change value of the temperature control energy consumption of the target building space over a first preset time period in the future based on the temperature control energy consumption related factors of the target building space to obtain predicted temperature control energy consumption change data, which can be used to determine the target cooling capacity 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 equipment for controlling the temperature of the target building space.

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

[0074] Specifically, the temperature control energy consumption related factors of the target building space may also include: historical temperature control energy consumption of the target building space, external meteorological data, external event information, etc. Specific external events include, for example, whether there are special gatherings of people.

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

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

[0077] The temperature control energy consumption related factors of the target building space are predicted through a neural network model, such as a long short-term memory network model, to obtain the above-mentioned predicted temperature control energy consumption change data.

[0078] Optionally, the execution of step 302 may be triggered based on a preset period. For example, the execution of step 302 may be triggered once every hour.

[0079] Optionally, the above-mentioned first preset time duration in the future can be set according to the usage scenario of the target building space. For example, for a commercial complex target building space whose usage changes in a 24-hour cycle, the above-mentioned first preset time duration can be set to 24 hours.

[0080] Specifically, when the flow of people in the target building space changes greatly, such as a subway station, the first preset time length can be set to a smaller value, such as 2 hours.

[0081] Optionally, the predicted temperature control energy consumption acquisition module predicts the energy consumption change data every 10 minutes in the next 24 hours based on the temperature control energy consumption related factors acquired in real time, and obtains the predicted temperature control energy consumption change data.

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

[0083] In an optional specific example, on a typical summer working day, at 2 a.m., it is determined based on the predicted temperature control energy consumption change data that a peak electricity consumption will occur 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 temperature control equipment in operation to store cooling capacity during low electricity price periods and reduce cooling capacity during peak electricity consumption periods, thereby obtaining the above target cooling 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 used to control the temperature control equipment in operation based on the target cooling capacity change data and the reported data sent by the edge computing device.

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

[0087] A temperature control device control instruction is generated based on the above target cooling capacity change data and the reported data, and the above control instruction 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 temperature control device in operation based on the target cooling capacity change data includes: determining the optimal operating load of the temperature control device in operation based on the target cooling capacity and the target energy efficiency ratio at the current target moment.

[0089] Optionally, the process of determining the optimal operating load of the temperature control device in operation based on the target cooling capacity and the target energy efficiency ratio at the current target moment includes determining the input power of the device in operation based on the following formula:

[0090]

[0091] Among them, COP represents the target energy efficiency ratio, Q represents the target cooling capacity at the current moment, and P represents the current input power;

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

[0093] Specifically, the above target energy efficiency ratio can be obtained from the equipment parameters of the temperature control equipment in operation.

[0094] Specifically, by determining the optimal operating load of the temperature control equipment in operation based on the target energy efficiency ratio, it can help ensure that while meeting the cooling demand, energy consumption is optimized and the equipment life is extended.

[0095] Optionally, when the reported data does not include abnormal evaluation result data of the operating parameters, the corresponding operating temperature control equipment is controlled based on the target cooling capacity change data so that the total operating load of the operating temperature control equipment is consistent with the target cooling capacity change data.

[0096] Optionally, there are multiple temperature control devices in operation.

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

[0098] Determine whether to change the number of operating temperature control devices based on the target cooling capacity change data; determine the optimal operating load of the operating temperature control devices based on the reported data; and regulate the operating status of the operating temperature control devices based on the optimal operating load.

[0099] Specifically, when the temperature control energy consumption value within the fourth preset time period predicted at the current moment becomes smaller than the corresponding temperature control energy consumption value predicted at the previous moment, the corresponding target cooling capacity is reduced, and the number of temperature control devices in operation can be reduced accordingly; when the temperature control energy consumption value within the fourth preset time period predicted at the current moment is larger than the corresponding temperature control energy consumption value predicted at the previous moment, the corresponding target cooling capacity is increased, and the number of temperature control devices in operation can be increased accordingly.

[0100] In an optional specific example, at 12:00 noon, it is predicted that the peak power consumption at 3 pm is higher than expected, and the corresponding target cooling capacity is also increased, so an additional chiller is added.

[0101] Specifically, the fourth preset duration is shorter than the first predicted duration.

[0102] Optionally, the edge computing device is as follows: Figure 2 As shown, it also includes: an operating parameter collection and preprocessing module, which is used to collect and obtain and preprocess the original detection value of the operating parameter at the current moment to obtain the current detection value; a reported data determination and sending module, which is also used to add the current detection value to the reported data.

[0103] Specifically, the process of preprocessing the original detection values ​​of the operating parameters includes: performing denoising processing on the original operating parameters.

[0104] Optionally, the operating parameters include current detection values ​​of vibration state parameters, temperature state parameters and pressure state parameters of the temperature control device during operation.

[0105] Optionally, the optimal operating load of the operating temperature control device is determined based on the reported data, including:

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

[0107] Specifically, the process of calculating the current health index of the running temperature control device based on the current detection values ​​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] Among them, HI represents the current health index of the equipment; w1, w2, w3 are the weights of different parameters, which can be determined in advance through experiments; T, V, P represent temperature state parameters, vibration state parameters and pressure state parameters respectively.

[0110] Optionally, the process of determining the optimal operating load of the temperature control device in operation based on the current health index includes, when the current health index exceeds the normal current health index of the corresponding device, initiating maintenance or adjustment operations, and setting the corresponding optimal operating load to a smaller value or 0 to reduce the operating load or shut down for maintenance, so as to avoid continuous deterioration of the rated health status of the temperature control device and affect the normal operation of the temperature control system.

[0111] Optionally, the reported data includes current abnormality assessment results of the operating temperature control equipment.

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

[0113] Specifically, when the current abnormality assessment result is a serious abnormality, the corresponding optimal operating load can be set to a smaller value or 0 to reduce the operating load or shut down for maintenance to avoid continuous deterioration of the rated health status of the temperature control equipment and affect the normal operation of the temperature control system.

[0114] Figure 4 A flow chart of a method for controlling the operation of a temperature control device provided in an embodiment of the present invention. This embodiment is applicable to a scenario in which the operation of a temperature control device in a target building space is controlled. The method can be executed by an edge computing device in the temperature control device operation control system provided in an embodiment of the present invention. The device can be implemented in software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device, such as a computer, a server, etc. The following embodiments will be described using the device integrated into an electronic device as an example. Reference Figure 4 , the method may specifically include the following steps:

[0115] Step 401, obtaining the current moving average value of the operating parameter based on the current detection value of the operating parameter of the operating temperature control device through the time window. This step can facilitate determining the abnormal evaluation result of the operating parameter based on the current moving average value.

[0116] Optionally, before step 401, the original detection value of the operating parameter at the current moment is collected and preprocessed to obtain the current detection value.

[0117] Optionally, before step 401, the current window length is determined based on the current abnormal frequency of the operating parameter, where the current abnormal frequency is the frequency of abnormalities in the operating parameter within the previous second preset time period.

[0118] Optionally, the above process of obtaining the current moving average value of the operating parameter based on the current detection value of the operating parameter of the running temperature control device through a time window includes: obtaining the current detection value and the current moving average value of the operating parameter through a time window with a length equal to the current window length.

[0119] Optionally, before obtaining the current detection value and the current moving average value of the operating parameter through the time window with the length of the current window length, the reference abnormal frequency of the operating parameter is determined based on the frequency of abnormalities in the operating parameter within a third preset time length in history; the process of determining the current window length based on the current abnormal frequency of the operating parameter includes: determining the current window length of the operating parameter based on the current abnormal frequency and the reference abnormal frequency of the operating parameter.

[0120] Step 402, based on the target abnormal value corresponding to the operating parameter and the current moving average, the current abnormality detection threshold of the operating parameter is determined, and based on the current detection value and the current abnormality detection threshold, the current abnormality assessment result of the operating parameter is determined; the target abnormal value is the historical abnormality detection value of multiple operating parameters, and this step adaptively and dynamically adjusts the abnormality detection threshold, which can better adapt to the changes in the operating parameters to improve the accuracy of abnormality detection.

[0121] Optionally, the above process of determining the current anomaly detection threshold of the operating parameter based on the target anomaly value corresponding to the operating parameter and the current moving average value includes: 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.

[0122] Step 403, determines the reporting data based on the current abnormal evaluation result, and sends the reporting data to the intelligent control device, so that the intelligent control device controls the running temperature control equipment based on the reporting data. This step can, on the basis of steps 401-402, reduce manual dependence, and timely and accurately know the abnormal parameters of the running temperature control equipment, thereby timely and accurately discovering the abnormal operation of the temperature control equipment, and further respond quickly to avoid the continuous deterioration of the operating status of the temperature control equipment.

[0123] Optionally, the process of determining the current abnormality assessment result of the operating parameter based on the current detection value and the current abnormality detection threshold includes:

[0124] The current abnormality assessment result is determined based on whether the current detection value deviates from the normal detection value range determined by the current abnormality detection threshold, the degree of deviation of the current detection value from the normal detection value range determined based on the current abnormality detection threshold, and / or the duration of the abnormality corresponding to the current detection value.

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

[0126] Optionally, the process of determining the reported data based on the current anomaly assessment result includes: determining the current detection value and the current anomaly assessment result as the content of the reported data.

[0127] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, 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 functional modules described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0128] An embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the temperature control device operation control method provided in any of the above embodiments is implemented.

[0129] An embodiment of the present invention further provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the temperature control device operation control method provided in any of the above embodiments is implemented.

[0130] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the temperature control device operation control method as described in any one of the embodiments of the present invention.

[0131] Reference below Figure 5 , which shows a schematic diagram of the structure of a computer system 500 of an electronic device suitable for implementing an embodiment of the present invention. Figure 5 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0132] like Figure 5As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 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 via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0133] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including 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 needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage section 508 as needed.

[0134] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-mentioned functions defined in the system of the present invention are executed.

[0135] It should be noted that the computer-readable medium shown in the present invention may 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 be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0136] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0137] The modules and / or units involved in the embodiments of the present invention may be implemented in software or hardware. The modules and / or units described may also be provided in a processor, for example, may be described as: a processor including a moving average acquisition module, an abnormal evaluation result acquisition module, and a reporting data determination and sending module. The names of these modules do not, in some cases, constitute limitations on the modules themselves.

[0138] As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device implements: obtaining the current moving average value of the operating parameter based on the current detection value of the operating parameter of the running temperature control device through a time window; determining 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, and determining the 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 multiple operating parameters; and

[0139] Reporting data is determined based on the current abnormality assessment result, and the reporting data is sent to the intelligent control device, so that the intelligent control device controls the running temperature control device based on the reporting data.

[0140] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A temperature control equipment operation control system, comprising an edge computing device, characterized in that: The edge computing device comprises: A moving average value acquisition module, used to acquire the current moving average value of the operating parameter based on the current detection value of the operating parameter of the operating temperature control device through a time window; an abnormality assessment 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 assessment 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 the operating parameters; and The reporting data determination and sending module is used to determine the reporting data based on the current abnormality assessment result, and send the reporting data to the intelligent control device, so that the intelligent control device controls the running temperature control device based on the reporting data.

2. The temperature control equipment operation control system according to claim 1, characterized in that: Also includes: The intelligent control device includes various temperature control devices of the target building space, and the intelligent control device includes: A predicted temperature control energy consumption acquisition module is used to predict the change value of the temperature control energy consumption of the target building space over a first preset time period in the future based on the temperature control energy consumption related factors of the target building space to obtain predicted temperature control energy consumption change data; a target cooling capacity acquisition module, configured to determine, based on the predicted temperature control energy consumption change data, a change value of the target cooling capacity of each temperature control device in the target building space over time within the first preset time period, and obtain target cooling capacity change data; and A control module is used to control the temperature control device in operation based on the target cooling capacity change data and the reported data sent by the edge computing device.

3. The temperature control equipment operation control system according to claim 1, characterized in that: The edge computing device further includes: A current window length acquisition module, used to determine the current window length based on the current abnormal frequency of the operating parameter, wherein the current abnormal frequency is the frequency at which the operating parameter is abnormal within the previous second preset time length; The moving average value acquisition module is used to acquire the current detection value and the current moving average value of the operating parameter through a time window with a length equal to the current window length.

4. The temperature control equipment operation control system according to claim 1, characterized in that: The determining 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 includes: The current anomaly detection threshold is calculated based on the difference between each target anomaly value and the current moving average value, and the current moving average value.

5. The temperature control equipment operation control system according to claim 3, characterized in that: Also includes: A reference abnormal frequency determination module, configured to determine a reference abnormal frequency of the operating parameter based on a frequency at which the operating parameter is abnormal within a third preset time period in history; The determining the current window length based on the current abnormal frequency of the operating parameter includes: determining the current window length of the operating parameter based on the current abnormal frequency of the operating parameter and the reference abnormal frequency.

6. The temperature control equipment operation control system according to claim 1, characterized in that: The determining the current abnormality assessment result of the operating parameter based on the current detection value and the current abnormality detection threshold comprises: The current abnormality assessment result is determined based on whether the current detection value deviates from the normal detection value range determined by the current abnormality detection threshold, the degree of deviation of the current detection value from the normal detection value range determined based on the current abnormality detection threshold, and / or the duration of the abnormality corresponding to the current detection value.

7. The temperature control equipment operation control system according to claim 1, characterized in that: The current abnormal assessment results include: slight abnormality, moderate abnormality and severe abnormality; The determining of reporting data based on the current abnormality assessment result includes: When the current abnormality assessment result is a moderate abnormality and / or a severe abnormality, the current abnormality assessment result is added to the reported data.

8. The temperature control equipment operation control system according to claim 2, characterized in that: The controlling the operating temperature control device based on the target cooling capacity change data and the reported data sent by the edge computing device includes: Determining whether to change the number of operating temperature control devices based on the target cooling capacity change data; Determining the optimal operating load of the operating temperature control device based on the reported data; and The operating state of the operating temperature control device is regulated based on the optimal operating load.

9. The temperature control equipment operation control system according to claim 2, characterized in that: The controlling the operating temperature control device based on the target cooling capacity change data includes: The optimal operating load of the operating temperature control device is determined based on the target cooling capacity and the target energy efficiency ratio at the current target moment.

10. The temperature control equipment operation control system according to claim 1, characterized in that: The edge computing device further includes: An operating parameter acquisition and preprocessing module is used to acquire and preprocess the original detection value of the operating parameter at the current moment to obtain the current detection value; The reported data determination and sending module is further used to add the current detection value to the reported data.

11. The temperature control equipment operation control system according to claim 10, characterized in that: The operating parameters include current detection values ​​of vibration state parameters, temperature state parameters and pressure state parameters of the temperature control device in operation; The determining the optimal operating load of the operating temperature control device based on the reported data includes: Calculating a current health index of the operating temperature control device based on current detection values ​​of the vibration state parameter, the temperature state parameter, and the pressure state parameter; as well as The optimal operating load of the operating temperature control device is determined based on the current health index.

12. The temperature control equipment operation control system according to claim 8, characterized in that: The reported data includes the current abnormality evaluation result of the operating temperature control device; The determining the optimal operating load of the operating temperature control device based on the reported data includes: The optimal operating load of the operating temperature control device is determined based on the corresponding current abnormality evaluation result.

13. A method for controlling the operation of a temperature control device, applied to an edge computing device of a temperature control device operation control system, characterized in that: include: Obtaining a current moving average value of the operating parameter based on a current detection value of the operating parameter of the operating temperature control device through a time window; Determining a 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, and determining a current abnormality assessment result of the operating parameter based on the current detection value and the current abnormality detection threshold; The target abnormal value is a historical abnormal detection value of a plurality of the operating parameters; as well as Reporting data is determined based on the current abnormality assessment result, and the reporting data is sent to the intelligent control device, so that the intelligent control device controls the running temperature control device based on the reporting data.

14. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the temperature control device operation control method as described in claim 13 is implemented.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the temperature control device operation control method as described in claim 13 is implemented.

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