Redundant air pressure compensation method, device and equipment for air conditioner refrigerant sensor

Abstract

The application provides a redundancy air pressure compensation method, device and equipment for an air conditioner refrigerant sensor, which comprises the following steps: collecting air pressure data according to a preset collection frequency in a first sampling period to obtain a first air pressure data set; determining whether the first air pressure data set is abnormal to obtain a first determination result; if the first determination result is no, performing a redundancy air pressure compensation operation based on the first air pressure data set, collecting air pressure data in a second sampling period according to a preset sub-period to obtain a second air pressure data set; dividing the second sampling period into several time periods with equal length, calculating the trend characteristics of each time period; determining whether there is an abnormality in the current second sampling period based on the trend characteristics of each time period to obtain a second determination result; and if the second determination result is yes, calling an initial effective air pressure value to perform a redundancy air pressure compensation operation. The application can accurately identify the implicit abnormality in the range and avoid compensation deviation caused by false data.

Description

Technical Field

[0001] This invention relates to the field of smart home appliances, and in particular to a method, apparatus and equipment for redundancy pressure compensation of an air conditioner refrigerant sensor. Background Technology

[0002] In gas concentration detection scenarios within air conditioning systems (such as residential air conditioners and commercial central air conditioning systems) (e.g., refrigerant leak detection), accurate measurement of gas concentration relies on real-time compensation of ambient air pressure. According to the ideal gas law PV=nRT (where P is gas pressure, V is volume, n is the amount of gas, R is a constant, and T is temperature), gas concentration (usually expressed as "amount of substance / volume," i.e., n / V) is directly related to gas pressure P. When temperature T remains constant, changes in gas pressure P will cause deviations in the detected gas concentration signal. Therefore, gas pressure compensation is a core element in ensuring the accuracy of gas concentration detection, directly impacting the safe operation of the air conditioning system (e.g., refrigerant leak warning) and user health (e.g., air quality monitoring).

[0003] Current mainstream air pressure compensation schemes have significant shortcomings: First, static compensation relying on external host-written parameters requires users to manually input altitude or air pressure values, which is prone to operational errors. Second, dynamic compensation using built-in air pressure sensors, while requiring no manual intervention, is susceptible to sensor failure due to hardware malfunctions, electromagnetic interference from air conditioning compressors, or high temperature and humidity environments, resulting in inaccurate data output. Furthermore, existing emergency strategies have significant flaws: concentration detection errors reach ±20% during uncompensated operation; when using fixed values ​​(e.g., 1013 hPa) as a substitute, the concentration after compensation is more than 55% higher in high-altitude areas (actual air pressure approximately 650 hPa), leading to false positives for refrigerant leaks. Simultaneously, data validity relies solely on range verification (e.g., 900-1100 hPa), failing to identify "hidden anomalies within the range," and continuous compensation of erroneous data leads to systemic biases; moreover, a dynamic recovery mechanism is lacking, with instantaneous sensor anomalies (e.g., a single instance of electromagnetic interference exceeding the range) being deemed "permanently failed," and switching to fixed values ​​degrades compensation accuracy.

[0004] Therefore, the existing redundant pressure compensation technology for air conditioning refrigerant sensors has the problem of poor compensation effect. Summary of the Invention

[0005] This invention provides a method, apparatus, and device for redundancy pressure compensation of an air conditioning refrigerant sensor, aiming to solve the problem of poor compensation effect in existing redundancy pressure compensation technologies for air conditioning refrigerant sensors.

[0006] In a first aspect, embodiments of the present invention provide a method for redundancy pressure compensation of an air conditioning refrigerant sensor, the method comprising:

[0007] When the refrigerant sensor is first powered on, it collects air pressure data according to a preset sampling frequency within a preset first sampling period to obtain the first air pressure dataset.

[0008] The first air pressure dataset is judged to be abnormal according to the preset data validity judgment strategy, and a first judgment result is obtained;

[0009] If the first judgment result is negative, then a redundant pressure compensation operation is performed based on the first pressure dataset, and pressure data is collected according to a preset sub-period within a preset second sampling period to obtain a second pressure dataset.

[0010] The second sampling period is divided into several time periods of equal duration, and the trend characteristics of each time period are calculated based on the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction;

[0011] Based on the trend characteristics of each time period, determine whether there is an anomaly in the current second sampling period, and obtain a second judgment result;

[0012] If the second judgment result is yes, then the pre-stored initial effective air pressure value is called to perform redundant air pressure compensation operation.

[0013] Secondly, embodiments of the present invention also provide a redundant pressure compensation device for an air conditioning refrigerant sensor, the device comprising:

[0014] The first acquisition unit is used to acquire air pressure data according to a preset acquisition frequency within a preset first sampling period when the refrigerant sensor is first powered on, and to obtain the first air pressure dataset.

[0015] The first judgment unit is used to judge whether the first air pressure dataset is abnormal according to a preset data validity judgment strategy, and to obtain a first judgment result.

[0016] The second acquisition unit is used to perform redundant pressure compensation operation based on the first pressure dataset if the first judgment result is negative, and to acquire pressure data according to a preset sub-period within a preset second sampling period to obtain the second pressure dataset.

[0017] The calculation unit is used to divide the second sampling period into several time periods of equal duration, and calculate the trend characteristics of each time period based on the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction;

[0018] The second judgment unit is used to determine whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period, and to obtain a second judgment result;

[0019] The execution unit is used to call the pre-stored initial effective air pressure value to perform redundant air pressure compensation operation if the second judgment result is yes.

[0020] Thirdly, embodiments of the present invention also provide an electronic device, which is a server or a terminal. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor corresponding to the server and the processor corresponding to the terminal execute the computer program simultaneously, the method described in the first aspect is implemented.

[0021] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the method described in the first aspect.

[0022] This invention provides a method, apparatus, and device for redundant pressure compensation of an air conditioning refrigerant sensor. The method includes: when the refrigerant sensor is first powered on, collecting pressure data according to a preset sampling frequency within a preset first sampling period to obtain a first pressure dataset; determining whether the first pressure dataset is abnormal according to a preset data validity determination strategy to obtain a first determination result; if the first determination result is negative, performing a redundant pressure compensation operation based on the first pressure dataset, and collecting pressure data according to a preset sub-period within a preset second sampling period to obtain a second pressure dataset; dividing the second sampling period into several time periods of equal duration, calculating the trend characteristics of each time period according to the second pressure dataset and a preset joint determination strategy; wherein the trend characteristics include fluctuation amplitude and trend direction; determining whether the current second sampling period is abnormal based on the trend characteristics of each time period to obtain a second determination result; if the second determination result is positive, calling a pre-stored initial valid pressure value to perform a redundant pressure compensation operation. This invention collects and verifies a first air pressure dataset, eliminating the need for manual input of air pressure parameters and avoiding operational errors at the source. It directly performs redundant air pressure compensation operations based on a valid first air pressure dataset. At the same time, it divides the second sampling period into several time periods and calculates the trend characteristics of each time period using a joint judgment strategy. This overcomes the limitations of single-range verification and can accurately identify hidden anomalies within the range caused by electromagnetic interference, minor sensor failures, etc., thus avoiding compensation deviations caused by erroneous data. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating the redundant pressure compensation method for an air conditioning refrigerant sensor provided in an embodiment of the present invention;

[0025] Figure 2 A schematic block diagram of a redundant pressure compensation device for an air conditioning refrigerant sensor provided in an embodiment of the present invention;

[0026] Figure 3 A schematic block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0029] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0030] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. Embodiments of this invention provide a method, apparatus, and device for redundancy pressure compensation of an air conditioning refrigerant sensor. For the redundancy pressure compensation method of this air conditioning refrigerant sensor, please refer to... Figure 1 , Figure 1 This is a flowchart illustrating a method for redundancy pressure compensation of an air conditioning refrigerant sensor provided in an embodiment of the present invention. The method is applied to the controller of an air conditioning system to achieve accurate redundancy pressure compensation for the refrigerant sensor.

[0031] Figure 1 This is a schematic flowchart illustrating the redundant pressure compensation method for an air conditioning refrigerant sensor provided in an embodiment of the present invention. Figure 1As shown, the method includes the following steps S110-S160.

[0032] S110. When the refrigerant sensor is first powered on, the pressure data is collected within the preset first sampling period according to the preset sampling frequency to obtain the first pressure data set.

[0033] In this embodiment, when the refrigerant sensor is first powered on, the air pressure data is collected within a preset first sampling period (e.g., 10 minutes) according to a preset sampling frequency (e.g., 1 second) to obtain the first air pressure dataset.

[0034] Furthermore, when the refrigerant sensor is first powered on, it is initialized, including checking whether the refrigerant sensor has feedback, resetting the chip according to preset requirements, and initializing registers such as conversion rate and resolution to meet the detection requirements.

[0035] After initialization, check if the fault flag associated with the refrigerant sensor is valid. If the fault flag is valid, determine if the pre-stored initial valid gas pressure value is valid. If the initial valid gas pressure value is valid, call the initial valid gas pressure value to perform redundant gas pressure compensation operation. If the initial valid gas pressure value is invalid, mark the refrigerant sensor as faulty and trigger a maintenance reminder so that maintenance personnel can handle it in time. If the fault flag is invalid, execute the step of collecting gas pressure data according to a preset sampling frequency within a preset first sampling period when the refrigerant sensor is first powered on to obtain the first gas pressure dataset.

[0036] S120. Determine whether the first air pressure dataset is abnormal according to the preset data validity determination strategy, and obtain the first determination result.

[0037] In this embodiment, the data validity determination strategy can be implemented in the following two ways: 1. By verifying point by point whether all the air pressure data in the first air pressure dataset are within a reasonable range, it can be determined whether the first air pressure dataset is abnormal; 2. Obtain the maximum value, minimum value and average air pressure of the first air pressure dataset; determine whether the maximum value, the minimum value and the average air pressure are all within the corresponding preset range, so as to determine whether the first air pressure dataset is abnormal.

[0038] In one embodiment, step S120 includes: obtaining the maximum value, minimum value, and average value of the first air pressure dataset; determining whether the maximum value, minimum value, and average value are all within the corresponding preset range; if the maximum value, minimum value, and average value are all within the corresponding preset range, then the first air pressure dataset is determined to be normal; if any one of the maximum value, minimum value, and average value exceeds the corresponding preset range, then the first air pressure dataset is determined to be abnormal.

[0039] In this embodiment, the maximum value, minimum value, and average value of the first air pressure dataset are obtained. Each of the maximum value, minimum value, and average value has a corresponding preset range. The abnormality of the first air pressure dataset can be determined by judging whether the maximum value, minimum value, and average value are all within their respective preset ranges. If the maximum value, minimum value, and average value are all within their respective preset ranges, the first air pressure dataset is determined to be normal. If any one of the maximum value, minimum value, or average value exceeds its corresponding preset range, the first air pressure dataset is determined to be abnormal.

[0040] In one embodiment, after step S120, the method further includes: if the first determination result is yes, then marking the refrigerant sensor as faulty and stopping the reading of the air pressure data collected by the refrigerant sensor.

[0041] In this embodiment, if the first judgment result is (the first air pressure dataset is abnormal), the refrigerant sensor is marked as faulty, and a maintenance reminder is triggered so that maintenance personnel can handle it in a timely manner.

[0042] S130. If the first judgment result is negative, then a redundant pressure compensation operation is performed based on the first pressure dataset, and pressure data is collected according to a preset sub-period within a preset second sampling period to obtain a second pressure dataset.

[0043] In this embodiment, if the first judgment result is negative (the first air pressure data is normal), a redundant air pressure compensation operation is performed based on the first air pressure dataset. Specifically, the average air pressure of the first air pressure dataset is obtained, and the average air pressure is used as the effective air pressure value to perform the redundant air pressure compensation operation. Within a preset second sampling period (if 24 hours or a multiple of 24 hours), air pressure data is collected according to a preset sub-period. The average value of the air pressure data collected within the preset sub-period is calculated. The average values ​​of all the preset sub-periods within the second sampling period are summarized to obtain the second air pressure dataset.

[0044] Furthermore, within a preset second sampling period (if 24h or a multiple of 24h), air pressure data is collected according to a preset sub-period; the average value of the air pressure data collected within the preset sub-period is calculated; the effective air pressure value is updated based on the average value of the preset sub-period, and a redundant air pressure compensation operation is performed based on the updated effective air pressure value.

[0045] In one embodiment, the step of collecting air pressure data according to a preset sub-period within a preset second sampling period to obtain a second air pressure dataset includes: collecting air pressure data according to a preset sub-period within the second sampling period; calculating the average value of the air pressure data collected within the preset sub-period; and summing up the average values ​​of all the preset sub-periods within the second sampling period to obtain the second air pressure dataset.

[0046] In this embodiment, assuming the second sampling period is 24 hours and the preset sub-period is 10 minutes, then 144 average values ​​can be obtained within the second sampling period, that is, the second air pressure dataset contains 144 average values.

[0047] S140. Divide the second sampling period into several time periods of equal duration, and calculate the trend characteristics of each time period based on the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction.

[0048] In this embodiment, the second sampling period is divided into several equal-length time periods. Specifically, the second sampling period can be divided into 6 equal-length time periods. The trend characteristics of each time period are calculated based on the second air pressure dataset and a preset joint determination strategy. Assuming the second sampling period is 24 hours and the preset sub-period is 10 minutes, then 144 average values ​​can be obtained within the second sampling period. If the second sampling period is divided into 6 equal-length time periods, each time period contains 24 average values. Based on the fluctuation amplitude calculation formula in the joint determination strategy and the average values ​​within each time period, the real-time fluctuation parameters of each time period can be calculated, and the fluctuation amplitude of the corresponding time period can be determined based on the real-time fluctuation parameters. Based on the linear regression formula in the joint determination strategy and the average values ​​within each time period, the slope of each time period is calculated, and the trend direction of the corresponding time period is determined based on the slope.

[0049] In one embodiment, step S140 includes: calculating the real-time fluctuation parameters of each time period according to a preset fluctuation amplitude calculation formula and the average value within each time period, and determining the fluctuation amplitude of the corresponding time period based on the real-time fluctuation parameters; calculating the slope of each time period according to a preset linear regression formula and the average value within each time period, and determining the trend direction of the corresponding time period based on the slope.

[0050] In this embodiment, assuming the second sampling period is 24 hours and the preset sub-period is 10 minutes, then 144 average values ​​can be obtained within the second sampling period. If the second sampling period is divided into 6 equal-length time periods, then each time period contains 24 average values, calculated according to the preset fluctuation amplitude formula ∆P.real =max(P 10min_real )−min(P 10min_real The real-time fluctuation parameter ∆P for each of the aforementioned time periods is calculated based on the average value within each time period. real The fluctuation amplitude corresponding to the time period is determined based on the real-time fluctuation parameters.

[0051] Assuming there are m data points ((t1, p1), (t2, p2), ..., (tm, pm)) within a certain time period (t is time, p is the average value), the expression of the linear regression formula is as follows:

[0052] k=(m∑(ti×pi)-∑ti∑pi) / (m∑(ti×ti)-(∑ti) 2 );

[0053] Where i = 1, 2, ..., m, ∑ is the accumulation symbol, and the time points t1, t2, ..., tm are all different. When the time points t1, t2, ..., tm are all different, m∑(ti×ti)-(∑ti) 2 ≠0.

[0054] Based on the linear regression formula and the average value within each time period, the slope k of each time period is calculated, and the trend direction of the corresponding time period is determined based on the slope. Specifically, if k > 0, the trend direction of the corresponding time period is upward; if k = 0, the air pressure has no obvious trend within the corresponding time period; if k < 0, the trend direction of the corresponding time period is downward.

[0055] S150. Based on the trend characteristics of each time period, determine whether there is an anomaly in the current second sampling period, and obtain a second judgment result.

[0056] In this embodiment, the trend features include fluctuation amplitude and trend direction. If the fluctuation amplitude is not within the preset fluctuation range, or if there are consecutive preset number of time periods and the trend direction is inconsistent with the corresponding baseline trend feature, then the second sampling period is determined to be abnormal. If the fluctuation amplitude is within the preset fluctuation range and there are no consecutive preset number of time periods and the trend direction is inconsistent with the corresponding baseline trend feature, then the second sampling period is determined to be normal.

[0057] Preferably, air pressure data is collected at a preset sampling frequency (e.g., 1 second) within a preset second sampling period, and the air pressure data collected each time is judged in real time to see if it is within the preset valid data range; if the number of data exceeding the valid data range in the continuously collected air pressure data reaches a preset threshold, the second sampling period is determined to be abnormal.

[0058] In one embodiment, step S150 includes: comparing the real-time fluctuation parameters of each time period with a preset fluctuation threshold; comparing the trend direction of each time period with the pre-stored baseline trend characteristics of the corresponding time period; if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold, or if there is a consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend characteristics, then it is determined that the current second sampling period is abnormal; if the second sampling period is abnormal, then the pre-stored initial effective air pressure value is called to perform redundant air pressure compensation operation.

[0059] In this embodiment, the real-time fluctuation parameters for each time period are... With the preset fluctuation threshold ( The baseline amplitude benchmark value (σ is the standard deviation of the baseline amplitude) is compared; the trend direction of each time period (obtained based on the slope k) is compared with the pre-stored baseline trend characteristics of the corresponding time period; within the second sampling period, if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold ( > If there are consecutive preset number (e.g., 3) of the time periods whose trend direction is inconsistent with the corresponding baseline trend characteristics (e.g., the trend direction is rising from 6 to 10, falling from 10 to 14, and rising from 14 to 18, while the baseline trend characteristics of the corresponding time periods on the same day are falling, rising, and falling respectively), then it is determined that there is an anomaly in the current second sampling period.

[0060] This invention performs dual-dimensional verification (amplitude + direction) on the second sampling period based on fluctuation threshold and historical baseline, thereby achieving accurate identification of hidden anomalies.

[0061] In one embodiment, after determining that there is an anomaly in the current second sampling period if the real-time fluctuation parameter of any of the time periods is greater than the fluctuation threshold, or if there are consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend feature, the method further includes: accumulating the number of invalid periods and returning to the step of collecting air pressure data according to preset sub-periods within the preset second sampling period to obtain a second air pressure dataset; if the number of invalid periods is detected to be greater than a preset number threshold, an anomaly flag is written to mark the refrigerant sensor as invalid and reading the air pressure data collected by the refrigerant sensor is stopped.

[0062] In this embodiment, the number of invalid cycles is accumulated, and the process returns to the step of collecting air pressure data according to a preset sub-cycle within a preset second sampling period to obtain a second air pressure dataset; if the number of invalid cycles is detected to be greater than a preset threshold, the refrigerant sensor is permanently determined to be faulty, and the refrigerant sensor can be marked as invalid by writing an abnormal flag, and the reading of air pressure data collected by the refrigerant sensor is stopped.

[0063] Furthermore, after the step of accumulating the number of invalid cycles and returning to the step of collecting air pressure data according to the preset sub-cycle within the preset second sampling period to obtain the second air pressure dataset, the method further includes: if the current second sampling period is abnormal, but the next subsequent second sampling period is normal, then the number of invalid cycles is cleared to zero, and the method returns to the step of collecting air pressure data according to the preset sub-cycle within the preset second sampling period to obtain the second air pressure dataset.

[0064] S160. If the second judgment result is yes, then the pre-stored initial effective air pressure value is called to perform redundant air pressure compensation operation.

[0065] In this embodiment, if there is an anomaly in the current second sampling period, the pre-stored initial effective air pressure value is invoked to perform a redundant air pressure compensation operation.

[0066] If the second judgment result is negative, then return to the step of collecting air pressure data according to the preset sub-period within the preset second sampling period to obtain the second air pressure dataset.

[0067] In summary, this invention collects and verifies a first atmospheric pressure dataset, eliminating the need for manual input of atmospheric pressure parameters and avoiding operational errors at the source. It directly performs redundant atmospheric pressure compensation operations based on a valid first atmospheric pressure dataset. Simultaneously, by dividing the second sampling period into several time periods and combining a joint judgment strategy to calculate the trend characteristics of each time period, it overcomes the limitations of single-range verification and can accurately identify latent anomalies within the range caused by electromagnetic interference, minor sensor failures, etc., thus avoiding compensation deviations caused by erroneous data.

[0068] Figure 2 This is a schematic block diagram of a redundant pressure compensation device for an air conditioning refrigerant sensor provided in an embodiment of the present invention. Figure 2 As shown, corresponding to the above-mentioned method for redundancy pressure compensation of air conditioning refrigerant sensors, this invention also provides a device for redundancy pressure compensation of air conditioning refrigerant sensors. This device is configured in the controller of the air conditioning system to achieve accurate redundancy pressure compensation of the refrigerant sensor. For details, please refer to... Figure 2 The redundant pressure compensation device 700 for the air conditioning refrigerant sensor includes:

[0069] The first acquisition unit 701 is used to acquire air pressure data according to a preset acquisition frequency within a preset first sampling period when the refrigerant sensor is first powered on, and to obtain the first air pressure dataset.

[0070] The first judgment unit 702 is used to judge whether the first air pressure dataset is abnormal according to a preset data validity judgment strategy, and to obtain a first judgment result.

[0071] The second acquisition unit 703 is used to perform redundant pressure compensation operation based on the first pressure dataset if the first judgment result is negative, and to acquire pressure data according to a preset sub-period within a preset second sampling period to obtain a second pressure dataset.

[0072] The calculation unit 704 is used to divide the second sampling period into several time periods of equal duration, and calculate the trend characteristics of each time period according to the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction;

[0073] The second judgment unit 705 is used to judge whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period, and to obtain a second judgment result;

[0074] The execution unit 706 is used to call the pre-stored initial effective air pressure value to perform redundant air pressure compensation operation if the second judgment result is yes.

[0075] In some embodiments, when the second acquisition unit 703 performs the step of acquiring air pressure data according to a preset sub-period within a preset second sampling period to obtain a second air pressure dataset, it is specifically used for:

[0076] Within the second sampling period, air pressure data is collected according to a preset sub-period; the average value of the air pressure data collected within the preset sub-period is calculated; and the average values ​​of all preset sub-periods within the second sampling period are summarized to obtain the second air pressure dataset.

[0077] In some embodiments, when the calculation unit 704 divides the second sampling period into several equal-length time periods and calculates the trend characteristics of each time period based on the second air pressure dataset and a preset joint determination strategy, the calculation unit 704 is specifically used for:

[0078] Based on the preset fluctuation amplitude calculation formula and the average value within each time period, the real-time fluctuation parameters of each time period are calculated, and the fluctuation amplitude of the corresponding time period is determined based on the real-time fluctuation parameters; based on the preset linear regression formula and the average value within each time period, the slope of each time period is calculated, and the trend direction of the corresponding time period is determined based on the slope.

[0079] In some embodiments, when the second judgment unit 705 performs the step of judging whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period and obtaining a second judgment result, it is specifically used for:

[0080] The real-time fluctuation parameters of each time period are compared with the preset fluctuation threshold; the trend direction of each time period is compared with the baseline trend characteristics of the corresponding time period in the pre-stored data; if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold, or if there is a consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend characteristics, then it is determined that there is an anomaly in the current second sampling period.

[0081] In some embodiments, after executing the step of determining that there is an anomaly in the current second sampling period if the real-time fluctuation parameter of any of the time periods is greater than the fluctuation threshold, or if there are consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend feature, the second determination unit 705 is further configured to:

[0082] The number of invalid cycles is accumulated, and the process returns to the step of collecting air pressure data according to a preset sub-cycle within a preset second sampling period to obtain a second air pressure dataset; if the number of invalid cycles is detected to be greater than a preset threshold, an anomaly flag is written to mark the refrigerant sensor as invalid, and the reading of air pressure data collected by the refrigerant sensor is stopped.

[0083] In some embodiments, when the first judgment unit 702 performs the step of judging whether the first air pressure dataset is abnormal according to a preset data validity judgment strategy and obtaining a first judgment result, it is specifically used for:

[0084] Obtain the maximum value, minimum value, and average value of the first air pressure dataset; determine whether the maximum value, minimum value, and average value are all within their respective preset ranges; if the maximum value, minimum value, and average value are all within their respective preset ranges, then the first air pressure dataset is determined to be normal; if any one of the maximum value, minimum value, and average value exceeds its respective preset range, then the first air pressure dataset is determined to be abnormal.

[0085] In some embodiments, when the first judgment unit 702 performs the step of judging whether the first air pressure dataset is abnormal according to a preset data validity judgment strategy and obtaining a first judgment result, it is specifically used for:

[0086] If the first judgment result is yes, then the refrigerant sensor is marked as faulty, and the reading of the air pressure data collected by the refrigerant sensor is stopped.

[0087] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the redundant pressure compensation device and each unit of the above-mentioned air conditioning refrigerant sensor can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0088] The aforementioned redundant pressure compensation device for the air conditioning refrigerant sensor can be implemented as a computer program, which can, for example... Figure 3 It runs on the electronic device shown.

[0089] Please see Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of the present invention. The electronic device 800 can be a terminal or a server. The terminal can be an electronic device with communication functions. The server can be a standalone server or a server cluster composed of multiple servers.

[0090] See Figure 3 The electronic device 800 includes a processor 802, a memory, and a network interface 805 connected via a system bus 801. The memory may include a non-volatile storage medium 803 and internal memory 804.

[0091] The non-volatile storage medium 803 may store an operating system 8031 ​​and a computer program 8032. The computer program 8032 includes program instructions that, when executed, cause the processor 802 to perform a redundancy pressure compensation method for an air conditioning refrigerant sensor.

[0092] The processor 802 provides computing and control capabilities to support the operation of the entire electronic device 800.

[0093] The internal memory 804 provides an environment for the operation of the computer program 8032 in the non-volatile storage medium 803. When the processor 802 corresponding to the server and the processor 802 corresponding to the terminal execute the computer program 8032 at the same time, a method for redundant pressure compensation of an air conditioning refrigerant sensor is implemented.

[0094] This network interface 805 is used for network communication with other devices. Those skilled in the art will understand that... Figure 3The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the electronic device 800 to which the present invention is applied. The specific electronic device 800 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0095] The processor 802 is used to run a computer program 8032 stored in the memory to perform the following steps:

[0096] When the refrigerant sensor is first powered on, air pressure data is collected at a preset sampling frequency within a preset first sampling period to obtain a first air pressure dataset. A preset data validity determination strategy is used to determine whether the first air pressure dataset is abnormal, resulting in a first determination result. If the first determination result is negative, a redundant air pressure compensation operation is performed based on the first air pressure dataset, and air pressure data is collected according to a preset sub-cycle within a preset second sampling period to obtain a second air pressure dataset. The second sampling period is divided into several equal-length time periods, and the trend characteristics of each time period are calculated based on the second air pressure dataset and a preset joint determination strategy. The trend characteristics include fluctuation amplitude and trend direction. Based on the trend characteristics of each time period, a determination is made whether the current second sampling period is abnormal, resulting in a second determination result. If the second determination result is positive, a pre-stored initial valid air pressure value is used to perform a redundant air pressure compensation operation.

[0097] In some embodiments, when the processor 802 acquires air pressure data according to a preset sub-period within a preset second sampling period to obtain a second air pressure dataset, the specific steps are as follows:

[0098] Within the second sampling period, air pressure data is collected according to a preset sub-period; the average value of the air pressure data collected within the preset sub-period is calculated; and the average values ​​of all preset sub-periods within the second sampling period are summarized to obtain the second air pressure dataset.

[0099] In some embodiments, when the processor 802 divides the second sampling period into several equal-length time periods and calculates the trend characteristics of each time period based on the second air pressure dataset and a preset joint determination strategy, wherein the trend characteristics include fluctuation amplitude and trend direction, the processor 802 specifically implements the following steps:

[0100] Based on the preset fluctuation amplitude calculation formula and the average value within each time period, the real-time fluctuation parameters of each time period are calculated, and the fluctuation amplitude of the corresponding time period is determined based on the real-time fluctuation parameters; based on the preset linear regression formula and the average value within each time period, the slope of each time period is calculated, and the trend direction of the corresponding time period is determined based on the slope.

[0101] In some embodiments, when the processor 802 determines whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period and obtains a second determination result, the processor 802 specifically implements the following steps:

[0102] The real-time fluctuation parameters of each time period are compared with the preset fluctuation threshold; the trend direction of each time period is compared with the baseline trend characteristics of the corresponding time period in the pre-stored data; if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold, or if there is a consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend characteristics, then it is determined that there is an anomaly in the current second sampling period.

[0103] In some embodiments, after implementing the step of determining that there is an anomaly in the current second sampling period if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold, or if there are consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend feature, the processor 802 further implements the following steps:

[0104] The number of invalid cycles is accumulated, and the process returns to the step of collecting air pressure data according to a preset sub-cycle within a preset second sampling period to obtain a second air pressure dataset; if the number of invalid cycles is detected to be greater than a preset threshold, an anomaly flag is written to mark the refrigerant sensor as invalid, and the reading of air pressure data collected by the refrigerant sensor is stopped.

[0105] In some embodiments, when the processor 802 implements the step of determining whether the first air pressure dataset is abnormal according to a preset data validity determination strategy and obtaining a first determination result, the following steps are specifically implemented:

[0106] Obtain the maximum value, minimum value, and average value of the first air pressure dataset; determine whether the maximum value, minimum value, and average value are all within their respective preset ranges; if the maximum value, minimum value, and average value are all within their respective preset ranges, then the first air pressure dataset is determined to be normal; if any one of the maximum value, minimum value, and average value exceeds its respective preset range, then the first air pressure dataset is determined to be abnormal.

[0107] In some embodiments, when the processor 802 implements the step of determining whether the first air pressure dataset is abnormal according to a preset data validity determination strategy and obtaining a first determination result, the following steps are specifically implemented:

[0108] If the first judgment result is yes, then the refrigerant sensor is marked as faulty, and the reading of the air pressure data collected by the refrigerant sensor is stopped.

[0109] It should be understood that, in this embodiment of the invention, the processor 802 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0110] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0111] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the following steps:

[0112] When the refrigerant sensor is first powered on, air pressure data is collected at a preset sampling frequency within a preset first sampling period to obtain a first air pressure dataset. A preset data validity determination strategy is used to determine whether the first air pressure dataset is abnormal, resulting in a first determination result. If the first determination result is negative, a redundant air pressure compensation operation is performed based on the first air pressure dataset, and air pressure data is collected according to a preset sub-cycle within a preset second sampling period to obtain a second air pressure dataset. The second sampling period is divided into several equal-length time periods, and the trend characteristics of each time period are calculated based on the second air pressure dataset and a preset joint determination strategy. The trend characteristics include fluctuation amplitude and trend direction. Based on the trend characteristics of each time period, a determination is made whether the current second sampling period is abnormal, resulting in a second determination result. If the second determination result is positive, a pre-stored initial valid air pressure value is used to perform a redundant air pressure compensation operation.

[0113] In one embodiment, when the processor executes the program instructions to collect air pressure data according to a preset sub-period within a preset second sampling period to obtain a second air pressure dataset, the specific steps are as follows:

[0114] Within the second sampling period, air pressure data is collected according to a preset sub-period; the average value of the air pressure data collected within the preset sub-period is calculated; and the average values ​​of all preset sub-periods within the second sampling period are summarized to obtain the second air pressure dataset.

[0115] In one embodiment, when the processor executes the program instructions to divide the second sampling period into several equal-length time periods, and calculates the trend characteristics of each time period based on the second air pressure dataset and a preset joint determination strategy, the specific implementation of the steps is as follows:

[0116] Based on the preset fluctuation amplitude calculation formula and the average value within each time period, the real-time fluctuation parameters of each time period are calculated, and the fluctuation amplitude of the corresponding time period is determined based on the real-time fluctuation parameters; based on the preset linear regression formula and the average value within each time period, the slope of each time period is calculated, and the trend direction of the corresponding time period is determined based on the slope.

[0117] In one embodiment, when the processor executes the program instructions to determine whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period and obtains a second determination result, the processor specifically implements the following steps:

[0118] The real-time fluctuation parameters of each time period are compared with the preset fluctuation threshold; the trend direction of each time period is compared with the baseline trend characteristics of the corresponding time period in the pre-stored data; if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold, or if there is a consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend characteristics, then it is determined that there is an anomaly in the current second sampling period.

[0119] In one embodiment, after executing the program instructions to determine that there is an anomaly in the current second sampling period if the real-time fluctuation parameter of any time period is greater than the fluctuation threshold, or if there are consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend feature, the processor further implements the following steps:

[0120] The number of invalid cycles is accumulated, and the process returns to the step of collecting air pressure data according to a preset sub-cycle within a preset second sampling period to obtain a second air pressure dataset; if the number of invalid cycles is detected to be greater than a preset threshold, an anomaly flag is written to mark the refrigerant sensor as invalid, and the reading of air pressure data collected by the refrigerant sensor is stopped.

[0121] In one embodiment, when the processor executes the program instructions to determine whether the first air pressure dataset is abnormal according to a preset data validity determination strategy and obtains a first determination result, the processor specifically implements the following steps:

[0122] Obtain the maximum value, minimum value, and average value of the first air pressure dataset; determine whether the maximum value, minimum value, and average value are all within their respective preset ranges; if the maximum value, minimum value, and average value are all within their respective preset ranges, then the first air pressure dataset is determined to be normal; if any one of the maximum value, minimum value, and average value exceeds its respective preset range, then the first air pressure dataset is determined to be abnormal.

[0123] In one embodiment, when the processor executes the program instructions to determine whether the first air pressure dataset is abnormal according to a preset data validity determination strategy and obtains a first determination result, the processor specifically implements the following steps:

[0124] If the first judgment result is yes, then the refrigerant sensor is marked as faulty, and the reading of the air pressure data collected by the refrigerant sensor is stopped.

[0125] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0126] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0127] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0128] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0129] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0130] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for redundancy pressure compensation of an air conditioning refrigerant sensor, characterized in that, The method includes: When the refrigerant sensor is first powered on, it is initialized. After initialization, the validity of the fault flag associated with the refrigerant sensor is checked. If the fault flag is valid, the validity of the pre-stored initial valid gas pressure value is determined. If the initial valid gas pressure value is valid, the initial valid gas pressure value is used to perform redundant gas pressure compensation operation. If the initial valid gas pressure value is invalid, the refrigerant sensor is marked as faulty, and a maintenance reminder is triggered. If the fault flag is invalid, gas pressure data is collected according to a preset sampling frequency within a preset first sampling period to obtain a first gas pressure dataset. The first air pressure dataset is judged to be abnormal according to the preset data validity judgment strategy, and a first judgment result is obtained; If the first judgment result is negative, then a redundant pressure compensation operation is performed based on the first pressure dataset, and pressure data is collected according to a preset sub-period within a preset second sampling period to obtain a second pressure dataset. The second sampling period is divided into several time periods of equal duration, and the trend characteristics of each time period are calculated based on the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction; Based on the trend characteristics of each time period, determine whether there is an anomaly in the current second sampling period, and obtain a second judgment result; If the second judgment result is yes, then the pre-stored initial effective air pressure value is called to perform redundant air pressure compensation operation; The second sampling period is divided into several equal-length time periods, and the trend characteristics of each time period are calculated based on the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction, including: Based on the preset fluctuation amplitude calculation formula and the average value within each time period, the real-time fluctuation parameters for each time period are calculated, and the fluctuation amplitude for the corresponding time period is determined based on the real-time fluctuation parameters. Based on the preset linear regression formula and the average value within each time period, the slope of each time period is calculated, and the trend direction of the corresponding time period is determined based on the slope.

2. The redundancy pressure compensation method for an air conditioning refrigerant sensor according to claim 1, characterized in that, The step of collecting air pressure data according to a preset sub-period within a preset second sampling period to obtain a second air pressure dataset includes: During the second sampling period, air pressure data is collected according to a preset sub-period; Calculate the average value of the air pressure data collected within the preset sub-cycle; The average values ​​of all the preset sub-cycles within the second sampling period are summed to obtain the second air pressure dataset.

3. The redundancy pressure compensation method for an air conditioning refrigerant sensor according to claim 1, characterized in that, The step of determining whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period, and obtaining a second determination result, includes: The real-time fluctuation parameters for each time period are compared with the preset fluctuation threshold. The trend direction of each time period is compared with the baseline trend characteristics of the corresponding time period in the pre-stored data. If the real-time fluctuation parameter of any of the time periods is greater than the fluctuation threshold, or if there are consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend feature, then it is determined that there is an anomaly in the current second sampling period.

4. The redundancy pressure compensation method for an air conditioning refrigerant sensor according to claim 3, characterized in that, If the real-time fluctuation parameter of any of the time periods is greater than the fluctuation threshold, or if there are consecutive preset number of time periods whose trend direction is inconsistent with the corresponding baseline trend feature, then after determining that there is an anomaly in the current second sampling period, the method further includes: The number of invalid cycles is accumulated, and the process returns to the step of collecting air pressure data according to the preset sub-cycle within the preset second sampling period to obtain the second air pressure dataset. If the number of invalid cycles detected is greater than a preset threshold, an anomaly flag is written to mark the refrigerant sensor as invalid, and the reading of the gas pressure data collected by the refrigerant sensor is stopped.

5. The redundancy pressure compensation method for an air conditioning refrigerant sensor according to claim 1, characterized in that, The step of determining whether the first air pressure dataset is abnormal according to a preset data validity determination strategy, and obtaining a first determination result, includes: Obtain the maximum, minimum, and average air pressure values ​​from the first air pressure dataset; Determine whether the maximum value, the minimum value, and the average air pressure are all within their respective preset ranges; If the maximum value, the minimum value, and the average air pressure are all within the corresponding preset range, then the first air pressure dataset is determined to be normal. If any of the maximum value, the minimum value, and the average air pressure exceeds the corresponding preset range, the first air pressure dataset is determined to be abnormal.

6. The redundancy pressure compensation method for an air conditioning refrigerant sensor according to claim 1, characterized in that, After determining whether the first air pressure dataset is abnormal according to a preset data validity determination strategy and obtaining a first determination result, the method further includes: If the first judgment result is yes, then the refrigerant sensor is marked as faulty, and the reading of the air pressure data collected by the refrigerant sensor is stopped.

7. A redundant pressure compensation device for an air conditioning refrigerant sensor, characterized in that, The device includes: The first acquisition unit is used to initialize the refrigerant sensor when it is first powered on. After initialization, it checks whether the fault flag associated with the refrigerant sensor is valid. If the fault flag is valid, it determines whether the pre-stored initial valid gas pressure value is valid. If the initial valid gas pressure value is valid, it calls the initial valid gas pressure value to perform redundant gas pressure compensation operation. If the initial valid gas pressure value is invalid, it marks the refrigerant sensor as faulty and triggers a maintenance reminder. If the fault flag is invalid, it collects gas pressure data according to a preset acquisition frequency within a preset first sampling period to obtain a first gas pressure dataset. The first judgment unit is used to judge whether the first air pressure dataset is abnormal according to a preset data validity judgment strategy, and to obtain a first judgment result. The second acquisition unit is used to perform redundant pressure compensation operation based on the first pressure dataset if the first judgment result is negative, and to acquire pressure data according to a preset sub-period within a preset second sampling period to obtain the second pressure dataset. The calculation unit is used to divide the second sampling period into several time periods of equal duration, and calculate the trend characteristics of each time period based on the second air pressure dataset and a preset joint judgment strategy; wherein, the trend characteristics include fluctuation amplitude and trend direction; The second judgment unit is used to determine whether there is an anomaly in the current second sampling period based on the trend characteristics of each time period, and to obtain a second judgment result; An execution unit is configured to, if the second determination result is yes, call the pre-stored initial effective air pressure value to perform a redundant air pressure compensation operation; The calculation unit is further configured to: calculate the real-time fluctuation parameters of each time period according to a preset fluctuation amplitude calculation formula and the average value within each time period; determine the fluctuation amplitude of the corresponding time period based on the real-time fluctuation parameters; calculate the slope of each time period according to a preset linear regression formula and the average value within each time period; and determine the trend direction of the corresponding time period based on the slope.

8. An electronic device, the electronic device being a server or terminal, the electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor corresponding to the server and the processor corresponding to the terminal execute the computer program simultaneously, the redundant pressure compensation method for the air conditioning refrigerant sensor as described in any one of claims 1-6 is implemented.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, cause the processor to perform the redundant pressure compensation method for an air conditioning refrigerant sensor as described in any one of claims 1-6.

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