Refrigerant leakage detection and control method, device and system and air conditioner

Abstract

The invention discloses a refrigerant leakage detection and control method, device and system and an air conditioner, and belongs to the field of air conditioners. The refrigerant leakage detection and control method comprises the steps that after multiple paths of sensor data are obtained, the sensor data are preprocessed to obtain target parameters, when the concentration of leaked gas is larger than preset concentration, a target control strategy is determined based on the target parameters, and finally control is conducted based on the target control strategy. According to the scheme, the sensor data is preprocessed instead of being directly used, the measurement result can be more accurate, whether the refrigerant leaks or not can be accurately judged, in addition, after the refrigerant leaks, a corresponding control mode can be adopted according to the target parameters, a proper control strategy is adopted under different conditions, and the refrigerant leakage detection accuracy is improved. And potential dangers caused by leakage can be effectively handled.

Description

Technical Field

[0001] The present application relates to the field of air conditioning technology, and in particular, to a refrigerant leakage detection and control method, device, system and air conditioner. Background Art

[0002] In recent years, with growing environmental awareness and advances in refrigerant technology, flammable refrigerants such as R290 (propane) and R32 (difluoromethane) have become increasingly popular alternatives to traditional CFCs in residential air conditioners due to their minimal ozone depletion and low global warming potential. However, these refrigerants are flammable and explosive. Refrigerants circulate between indoor and outdoor unit pipes, and due to vibration, age, and other factors, welds can leak into the room. Leaks can cause fires or explosions and pose health risks.

[0003] Currently, existing technologies for leak detection and explosion prevention of flammable refrigerants primarily rely on traditional sensors and simple alarm systems. While these methods can detect refrigerant leaks to a certain extent, they suffer from issues such as insufficient sensitivity, high false alarm rates, and slow response times, making them inadequate for the safety and reliability required of household air conditioners. Furthermore, existing explosion prevention measures are typically limited to power outages or activating exhaust systems, lacking intelligent and coordinated control strategies, making them ineffective in addressing potential hazards posed by leaks. Summary of the Invention

[0004] In order to overcome the shortcomings of the existing technology, the present application provides a refrigerant leakage detection and control method, device, system and air conditioner to solve the problems of insufficient sensitivity, high false alarm rate, slow response speed, etc. of the existing refrigerant leakage detection scheme, and the existing explosion-proof control means are usually limited to cutting off the power supply or starting the exhaust device, lacking intelligent and coordinated control strategies, and unable to effectively deal with the potential dangers caused by leakage.

[0005] The technical solution adopted by this application to solve its technical problems is:

[0006] In a first aspect, a refrigerant leakage detection and control method is provided, comprising:

[0007] Acquire data from multiple sensors, wherein the multiple sensors include at least a pressure sensor, a temperature sensor, and a gas concentration sensor;

[0008] Preprocessing the sensor data to obtain target parameters, the target parameters including: leakage gas concentration, system pressure, and heat exchanger surface temperature;

[0009] When the leakage gas concentration is greater than a preset concentration, determining a target control strategy based on the target parameter;

[0010] Control is performed based on the target control strategy.

[0011] As an optional implementation of the present application, the preprocessing of the sensor data to obtain the target parameter includes:

[0012] Get the analog signal collected by the sensor;

[0013] Convert the analog signals into digital signals, and perform filtering and calibration;

[0014] Determine the current moment's measurement value based on the measurement value determined at the previous moment and the data acquired at the current moment; current moment's measurement value = previous moment's measurement value * (1 - preset weight coefficient) + preset weight coefficient * current moment's acquired data;

[0015] A target parameter is obtained based on the measured values.

[0016] As an optional implementation of the present application, the preprocessing of the sensor data to obtain the target parameter includes:

[0017] Setting the initial state estimate and the initial error covariance matrix P0; define the state transfer matrix A, the control input matrix B, the observation matrix H, the process noise covariance matrix Q and the observation noise covariance matrix R;

[0018] For each time step k, predict the state and error covariance matrix at the next moment:

[0019]

[0020] P k|k-1 =AP k-1|k-1 A T +Q

[0021] in, is the state prediction estimate for the kth time step based on the information of the k-1th time step, is the state update estimate of the k-1th time step based on the information of the k-1th time step, u k is the control input vector; P k|k-1 is the prediction error covariance matrix of the kth time step based on the information of the k-1th time step; P k-1|k-1 is the updated error covariance matrix of the k-1th time step obtained based on the information of the k-1th time step;

[0022] Update each measurement value and update the measurement values ​​of multiple sensors and P k|k :

[0023] Kk =P k|k-1 H T (HP k|k-1 H T +R) -1

[0024]

[0025] P k|k =(IK k H)P k|k-1

[0026] Among them, K k is the gain at the kth time step, Z k is the measurement value at the kth time step, is the updated state estimate of the kth time step based on the information of the kth time step, P k|k The updated error covariance matrix of the kth time step is obtained based on the information of the kth time step, where I is the identity matrix;

[0027] Will as the target parameter at the kth time step.

[0028] As an optional implementation of the present application, when the leakage gas concentration is greater than a preset concentration, determining a target control strategy based on the target parameter includes:

[0029] When the concentration of the leaked gas is greater than a preset concentration, the leakage duration during which the concentration of the leaked gas is greater than the preset concentration is obtained, and the pressure difference between the system pressure and the calibration pressure is calculated, as well as the temperature difference between the surface temperature of the heat exchanger and the theoretical temperature is calculated;

[0030] A target control strategy is determined based on the leakage duration, the pressure difference, and the temperature difference range.

[0031] As an optional implementation of the present application, determining the target control strategy based on the leakage duration, the pressure difference, and the temperature difference range includes:

[0032] When the leakage duration is less than or equal to a first preset duration, the pressure difference is less than or equal to a first preset pressure difference, and the temperature difference is less than or equal to the first preset pressure difference, determining that the target control strategy is at least one of the following: sending an alarm, obtaining a leakage location;

[0033] When the leakage duration is greater than a first preset duration and less than a second preset duration, or the pressure difference is greater than a first preset pressure difference and less than a second preset pressure difference, or the temperature difference is greater than the first preset pressure difference and less than the second preset pressure difference, determining the target control strategy to be at least one of the following: shutting down the compressor, starting emergency ventilation, and sending a maintenance notice;

[0034] When the leakage duration is greater than or equal to the second preset duration, or the pressure difference is greater than or equal to the second preset pressure difference, or the temperature difference is greater than or equal to the second preset pressure difference, the target control strategy is determined to be at least one of the following: emergency shutdown, remote alarm.

[0035] As an optional implementation of this application, the following is also included:

[0036] Acquire sound waves based on ultrasonic sensors;

[0037] When the sound wave is determined to be generated by refrigerant leakage based on the frequency of the sound wave, the leakage location is determined based on data from at least three ultrasonic sensors, where the data from the ultrasonic sensors include: the earliest reception time of the same sound wave and the location of each ultrasonic sensor.

[0038] As an optional implementation of this application, the following is also included:

[0039] When the concentration of the leaked gas is greater than a preset concentration, determining a target historical moment with the same target parameters as the current target parameters in the historical moments;

[0040] Obtaining control parameters of the target historical moment, the control parameters including a target refrigerant charge amount;

[0041] Control is performed based on the control parameters.

[0042] In a second aspect, a refrigerant leakage detection and control device is provided, comprising:

[0043] A sensor data acquisition module is used to acquire data from multiple sensors, wherein the multiple sensors include at least a pressure sensor, a temperature sensor, and a gas concentration sensor;

[0044] A target parameter acquisition module is used to pre-process the sensor data to obtain target parameters, wherein the target parameters include: leakage gas concentration, system pressure, and heat exchanger surface temperature;

[0045] a control strategy determination module, configured to determine a target control strategy based on the target parameter when the leakage gas concentration is greater than a preset concentration;

[0046] The refrigerant leakage control module is used to perform control based on the target control strategy.

[0047] In a third aspect, a refrigerant leakage detection and control system is provided, comprising:

[0048] at least one processor and at least one memory;

[0049] The memory stores executable instructions of the processor;

[0050] The processor is configured to execute any of the above-mentioned refrigerant leakage detection and control methods.

[0051] In a fourth aspect, an air conditioner is provided, applying any of the above-mentioned refrigerant leakage detection and control methods.

[0052] Beneficial effects:

[0053] The technical solution of the present application provides a refrigerant leakage detection and control method, device, system and air conditioner. Among them, the refrigerant leakage detection and control method includes, after obtaining multi-channel sensor data, pre-processing the sensor data to obtain target parameters, when the leakage gas concentration is greater than the preset concentration, determining a target control strategy based on the target parameters, and finally controlling based on the target control strategy. The present application solution pre-processes the sensor data instead of using it directly, which can make the measurement results more accurate, and thus accurately determine whether the refrigerant has leaked. In addition, after the refrigerant leaks, the corresponding control method can be adopted according to the target parameters. In different situations, appropriate control strategies can be adopted to effectively deal with potential dangers caused by the leak. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0055] Figure 1 This is a flow chart of a refrigerant leakage detection and control method provided in an embodiment of the present application;

[0056] Figure 2 This is a schematic structural diagram of a household air-conditioning refrigerant circulation system provided in an embodiment of the present application;

[0057] Figure 3 This is a schematic diagram of a refrigerant leakage detection control using multiple sensors provided in an embodiment of the present application;

[0058] Figure 4 This is a flow chart of a specific refrigerant leakage detection and control method provided in an embodiment of the present application;

[0059] Figure 5 This is a schematic structural diagram of a refrigerant leakage detection and control device provided in an embodiment of the present application;

[0060] Figure 6 This is a structural diagram of a refrigerant leakage detection and control system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application are described in detail below with reference to the accompanying drawings and examples. Obviously, the described embodiments are only some of the embodiments of this application, rather than all of them. Based on the embodiments in this application, all other implementation methods obtained by ordinary technicians in this field without making any creative work are within the scope of protection of this application.

[0062] Reference Figure 1 The present invention provides a refrigerant leakage detection and control method for use in refrigeration equipment such as air conditioners or refrigerators. The method includes:

[0063] S11: Acquire data from multiple sensors, where the multiple sensors include at least a pressure sensor, a temperature sensor, and a gas concentration sensor;

[0064] Among them, the pressure sensor is used to obtain the system pressure, such as the system high pressure;

[0065] The temperature sensor is used to obtain the surface temperature of the heat exchanger, such as the surface temperature of the evaporator and / or condenser;

[0066] The gas concentration sensor is used to obtain the concentration of leaked gas.

[0067] In addition, it can also include ultrasonic sensors, compressor current sampling sensors, infrared sensors, and temperature and humidity sensors.

[0068] The installation position of each sensor is set according to actual needs.

[0069] In order to reduce interference, the embodiment of the present application installs the sensor on a shock-proof sensor bracket to avoid false detection or detection fluctuations caused by vibration.

[0070] S12: Preprocessing the sensor data to obtain target parameters, where the target parameters include leakage gas concentration, system pressure, and heat exchanger surface temperature.

[0071] It should be noted that the data obtained by the sensor is an analog signal, which needs to be converted into a digital signal by a digital-to-analog conversion module and then filtered and calibrated.

[0072] In practice, the value obtained after the above operation is not accurate, which seriously affects the detection effect. Therefore, as a preferred implementation method of the present application, the measurement value at the current moment is determined based on the measurement value determined at the previous moment and the data obtained at the current moment; the details are as follows:

[0073] Current moment measurement value = previous moment measurement value * (1-preset weight coefficient) + preset weight coefficient * current moment acquisition data.

[0074] The preset weight coefficient is a positive number less than 1 and is set according to actual needs.

[0075] After the above processing, the obtained measured value is closer to the true value and can effectively provide a control effect.

[0076] In addition, in order to obtain more accurate target parameters, this application also includes:

[0077] Setting the initial state estimate and the initial error covariance matrix P0; define the state transfer matrix A, the control input matrix B, the observation matrix H, the process noise covariance matrix Q and the observation noise covariance matrix R;

[0078] For each time step k, predict the state and error covariance matrix at the next moment:

[0079]

[0080] P k|k-1 =AP k-1|k-1 A T +Q

[0081] in, is the state prediction estimate for the kth time step based on the information of the k-1th time step, is the state update estimate of the k-1th time step based on the information of the k-1th time step, u k is the control input vector; P k|k-1 is the prediction error covariance matrix of the kth time step based on the information of the k-1th time step; P k-1|k-1 is the updated error covariance matrix of the k-1th time step obtained based on the information of the k-1th time step;

[0082] Update each measurement value and update the measurement values ​​of multiple sensors and P k|k :

[0083] K k =P k|k-1 H T (HP k|k-1 H T+R) -1

[0084]

[0085] P k|k =(IK k H)P k|k-1

[0086] Among them, K k is the gain at the kth time step, Z k is the measurement value at the kth time step, which can be the measurement value calculated after the preset weight coefficient, or the measurement value obtained directly from the sensor. is the updated state estimate of the kth time step based on the information of the kth time step, P k|k The updated error covariance matrix of the kth time step is obtained based on the information of the kth time step, where I is the identity matrix;

[0087] Will as the target parameter at the kth time step.

[0088] That is, the present application solution can effectively reduce the noise and interference of the sensor measurement value through the above algorithm, ensuring that the target parameter finally obtained can truly represent the real value.

[0089] S13: When the leakage gas concentration is greater than a preset concentration, determining a target control strategy based on the target parameter;

[0090] When the concentration of leaked gas is greater than the preset concentration, there is a risk of explosion, so further control is required.

[0091] Specifically, when the concentration of the leaked gas is greater than a preset concentration, the leakage time during which the concentration of the leaked gas is greater than the preset concentration is obtained, and the pressure difference between the system pressure and the calibration pressure is calculated, and the temperature difference between the surface temperature of the heat exchanger and the theoretical temperature is calculated;

[0092] A target control strategy is determined based on the leakage duration, the pressure difference, and the temperature difference range.

[0093] Exemplarily, determining a target control strategy based on the leakage duration, the pressure difference, and the temperature difference range includes:

[0094] When the leakage duration is less than or equal to a first preset duration, the pressure differential is less than or equal to a first preset pressure differential, and the temperature differential is less than or equal to a first preset pressure differential, the target control strategy is determined to be the first control strategy. The first control strategy includes at least one of the following: sending an alarm and obtaining the leak location. In other words, the first control strategy is only adopted when all three conditions are met. In this case, the leakage is not serious and can likely be resolved by the user. This eliminates the need to disconnect the power supply or shut down the compressor, thus ensuring system uptime while ensuring operational safety and improving the user experience.

[0095] When the leakage duration is greater than the first preset duration and less than the second preset duration, or the pressure difference is greater than the first preset pressure difference and less than the second preset pressure difference, or the temperature difference is greater than the first preset pressure difference and less than the second preset pressure difference, the target control strategy is determined to be the second control strategy, and the second control strategy includes at least one of the following: shutting down the compressor, starting emergency ventilation, and sending a maintenance notification; that is, when one of the above three conditions is met, the second control strategy is adopted.

[0096] If the leakage duration is greater than or equal to the second preset duration, or the pressure difference is greater than or equal to the second preset pressure difference, or the temperature difference is greater than or equal to the second preset pressure difference, the target control strategy is determined to be a third control strategy. The third control strategy includes at least one of the following: emergency shutdown and remote alarm. That is, the third control strategy is adopted when one of the above three conditions is met.

[0097] It is understood that the determination conditions of the third control strategy have the highest priority. For example, if the pressure difference is greater than the first preset pressure difference and less than the second preset pressure difference, and the temperature difference is greater than the first preset pressure difference and less than the second preset pressure difference, but the leakage duration is greater than or equal to the second preset duration, the third control strategy will be adopted. Although two of the conditions of the second control strategy are met, the third control strategy will be adopted first because its determination conditions have the highest priority. Only after it is determined that the third control strategy is not met will the second control strategy be determined.

[0098] Alternatively, when the leakage duration is greater than or equal to the second preset duration, or the pressure difference is greater than or equal to the second preset pressure difference, or the temperature difference is greater than or equal to the second preset pressure difference, the target control strategy is determined to be the third control strategy, and the third control strategy includes at least one of the following: emergency shutdown, remote alarm.

[0099] In other cases, a second control strategy is determined, and the second control strategy includes at least one of the following: shutting down the compressor, starting emergency ventilation, and sending a maintenance notice.

[0100] It should be noted that it also includes:

[0101] Acquire sound waves based on ultrasonic sensors;

[0102] When the sound wave is determined to be generated by refrigerant leakage based on the frequency of the sound wave, the leakage location is determined based on data from at least three ultrasonic sensors, where the data from the ultrasonic sensors include: the earliest reception time of the same sound wave and the location of each ultrasonic sensor.

[0103] In addition, it should be noted that different refrigerant types have different preset concentrations.

[0104] Because different types of flammable refrigerants are used for different models in existing control schemes, different detection data need to be switched to implement the control method, which lacks universality of the control method.

[0105] In order to achieve more unified control, in one embodiment of the present application, a micro gas analyzer is added to the gaseous refrigerant discharge port of the compressor to detect gas composition, and then a preset concentration is determined based on other components, facilitating personalized control of different refrigerant types.

[0106] S14: Control is performed based on the target control strategy.

[0107] Additionally, it includes:

[0108] When the concentration of the leaked gas is greater than a preset concentration, determining a target historical moment with the same target parameters as the current target parameters in the historical moments;

[0109] Obtaining control parameters of the target historical moment, the control parameters including a target refrigerant charge amount;

[0110] Control is performed based on the control parameters.

[0111] For example, after a refrigerant leak is detected and an early warning is issued, all data from the entire period of use of the air conditioning system (sensor data, data generated by the algorithm, and system user settings) is saved and combined with refrigerant charge management. When the system detects or predicts the same data next time, it can proactively adjust the refrigerant charge to reduce the refrigerant gas pressure in the pipeline to prevent the copper pipe welding points from being damaged due to excessive pressure and refrigerant gas leakage. The key point is to combine the data after the leak warning with dynamic refrigerant charge control to effectively prevent leaks.

[0112] The refrigerant leak detection and control method provided in the embodiment of the present application, after acquiring multi-channel sensor data, pre-processes the sensor data to obtain target parameters. When the leaked gas concentration is greater than a preset concentration, a target control strategy is determined based on the target parameters, and finally control is performed based on the target control strategy. The present application scheme pre-processes the sensor data instead of directly using it, which can make the measurement results more accurate, and thus accurately determine whether the refrigerant has leaked. In addition, after the refrigerant leaks, the corresponding control method can be adopted according to the target parameters. In different situations, the appropriate control strategy can be adopted to effectively deal with the potential dangers caused by the leak.

[0113] In order to illustrate the present application scheme in more detail, a specific implementation scheme is provided below using a household air conditioner as an example.

[0114] Traditional household air conditioning refrigerant circulation system such as Figure 2 As shown, since this application does not improve its circulation loop and principle, it will not be described in detail here.

[0115] like Figure 3 As shown, this application solution uses multiple sensors to detect refrigerant leakage. The outdoor unit is equipped with sensors including:

[0116] The pressure sensor monitors the real-time pressure on the high-pressure side of the air-conditioning system to determine pressure abnormalities;

[0117] The temperature sensor monitors the evaporator surface temperature and condenser temperature, and determines leakage by the difference with the theoretical value.

[0118] Current sampling monitoring determines abnormal compressor current fluctuations;

[0119] The gas analyzer is a miniature device that can be directly installed on the refrigerant pipeline of the air-conditioning system for real-time monitoring.

[0120] The indoor unit is equipped with sensors including infrared sensors to monitor the indoor area and temperature and humidity sensors to monitor the indoor temperature and humidity to eliminate interference.

[0121] The gas concentration sensor uses an NDIR infrared sensor, and each sensor is placed in the corresponding position. Dual sensor cross-validation is performed (that is, when the same type of sensor is in use, due to the possibility of a single failure or error, two sensors are selected for cross-validation. This can avoid false alarms caused by data errors and ensure data accuracy) to prevent single point failure. A shock-proof sensor bracket is used, combined with an algorithm to filter out false alarms caused by vibration.

[0122] Collected sensor data is transmitted to the MCUs of the indoor and outdoor units. The MCUs read the data, process it through algorithms, determine the leakage level, and take appropriate protective control actions based on the leakage level. An alarm is sounded, a fault code is displayed on the display panel, and the user is notified of the need for inspection and repair via the cloud server. This data is then stored and, based on user habits, optimized through machine learning algorithms to achieve dynamic adjustments and refrigerant charge management.

[0123] Specific refrigerant leakage detection and control methods are as follows: Figure 4 As shown:

[0124] The air conditioner is powered on to perform self-test and calibration of each sensor, the unit is powered on and the compressor starts.

[0125] After the refrigerant is compressed into a gaseous state by the compressor and released from the pipeline, it passes through a gas analyzer to monitor the refrigerant type used by the unit. This information is first transmitted to the MCU, which then adjusts the data collected by each sensor and the leakage level determination parameters based on the detected refrigerant type. (This is because different flammable refrigerants have different lower explosion limits (LELs), explosion ranges, different accuracy requirements for monitoring sensors, and different properties at different temperatures and humidities.)

[0126] After adjustment, the MCU collects the analog signal from the sensor through the ADC module, converts it into a digital signal, and then performs filtering and calibration, as well as data preprocessing. The preprocessing is carried out in the following way:

[0127] New value = old value × (1-α) + X × α

[0128] Among them, α is the weight coefficient, α is less than 1, and X is the latest sensor data.

[0129] After the collected data is processed, the data collected and processed by all sensors are fused through algorithms, which can comprehensively utilize the information of multiple sensors, reduce the impact of noise, and improve the accuracy of estimation.

[0130] The algorithm combines the measurement data from multiple sensors into the update step of the algorithm to obtain a more accurate and reliable state estimate. The specific steps are as follows:

[0131] initialization:

[0132] Setting the initial state estimate and the initial error covariance matrix P0.

[0133] Define the state transfer matrix A, control input matrix B, observation matrix H, process noise covariance matrix Q and observation noise covariance matrix R.

[0134] Prediction steps:

[0135] For each time step k, predict the state and error covariance matrix at the next moment

[0136]

[0137] P k|k-1 =AP k-1|k-1 A T +Q

[0138] u k It is the control input vector, which represents the external control input (such as command, instruction or drive signal) applied to the system at the kth time step in the algorithm. For example, in an air-conditioning system, it can be the speed of the compressor, the valve opening, etc. It describes the external influence on the system state and is used to model the system dynamics. It is usually known and associated with the set point, user input or other operations in the control system. Of course, it can also be measured by sensors (such as compressor speed). In the prediction step, it is used to calculate the state estimate at the next moment, reflecting the impact of the external control signal on the system;

[0139] Update steps:

[0140] Update the measurement value of each sensor.

[0141] Integrate measurements from multiple sensors to update state estimates and the error covariance matrix P k|k .

[0142] Update formula: K k =P k|k-1 H T (HP k|k-1 H T +R) -1

[0143]

[0144] P k|k =(IK k H)P k|k-1

[0145] K k is the Kalman gain. Z k : The measurement value at the kth time step, representing the actual data detected by the sensor. I indicates that the identity matrix is ​​a square matrix with 1 on the diagonal and 0 on the rest of the elements.

[0146] (The subscripts in the above formula mean:

[0147] k: current time step;

[0148] k-1: previous time step;

[0149] |k-1: prediction based on information from the previous time step;

[0150] |k: Update based on the measurement value of the current time step;

[0151] example: The state prediction estimate at the kth time step is based on the state information at the previous time step.

[0152] The state update estimate for the kth time step, combined with the measurement value of the current time step.

[0153] P k|k-1 : The forecast error covariance matrix at the kth time step, representing the uncertainty of the forecast estimate.

[0154] P k|k : The updated error covariance matrix at the kth time step, representing the uncertainty of the updated estimate. )

[0155] The more accurate and reliable data after the algorithm is integrated is used to develop a leakage level classification model. First, the classification parameters are set, including pressure anomaly ΔP (the difference between the real-time pressure and the calibration pressure), temperature anomaly ΔT (the difference between the evaporator surface temperature and the theoretical value), gas concentration exceeding the threshold (R290 threshold: 5% to 10% LEL, LEL = 2.1%;

[0156] R32 threshold: 10% to 25% LEL, LEL = 14.4%) duration, dynamic indicators such as the current fluctuation rate of change, temperature change rate, etc. (These dynamic indicators can be used as indicators of classification parameters, but too many indicators can lead to system misjudgment. Therefore, more accurate and reliable pressure and temperature indicator data are used to establish the leakage level classification model. Other indicators can be used as background data storage for updating the algorithm when the system triggers an alarm. LEL (Lower Explosion Limit) is the concentration unit of the lower explosion limit of combustible gas, indicating the lowest volume percentage concentration of combustible gas in air that can cause an explosion.

[0157] Initially set the grading standard value, and set an initial threshold for each grading parameter under the corresponding grading:

[0158] Level 1 (minor leakage): ΔP ≤ 10% of the calibration value, ΔT ≤ 5°C, and the concentration exceeds the standard briefly (< 1 min).

[0159] Level 1 response: trigger an alarm, record the leak location, and advise the user to check.

[0160] Level 2 (moderate leakage): 10% < ΔP < 20%, ΔT > 5°C, concentration exceeds the standard continuously (> 1 min) (one of which is reached and determined as a moderate leakage).

[0161] Level 2 response: Shut down the compressor, start emergency ventilation, and notify maintenance.

[0162] Level 2 (serious leakage): ΔP ≥ 20%, ΔT ≥ 10°C, and the concentration exceeds the standard continuously (>5min).

[0163] Level 3 response: emergency shutdown, remote alarm.

[0164] When a refrigerant leak occurs, pressure generates high-frequency sound waves. Multiple ultrasonic sensors are deployed around the pipes to form a coverage network. These sensors capture the high-frequency sound waves generated by the leak in real time. By compensating for time difference and velocity, the leak location is determined. Combined with multiple sensors, the ultrasonic positioning algorithm accurately locates the refrigerant leak. The refrigerant leak data and the leak location are stored on a cloud server and sent to the user. Ultrasonic sensors are used to locate refrigerant leaks. The following algorithm can be used:

[0165] Triangulation positioning method: Utilize the time difference and propagation speed of three sensors to calculate the coordinates of the leakage point through geometric formulas.

[0166] Combined with historical leakage data, the threshold, data processing weight coefficient and data fusion weight are dynamically adjusted. At the same time, combined with user usage habits, the refrigerant filling amount is dynamically adjusted. When the user is in use, the system dynamically adjusts the refrigerant filling amount transported by the compressor to the pipeline based on historical data, which can also reduce the pipeline pressure and effectively avoid refrigerant leakage.

[0167] Dynamic adjustment of refrigerant charge is an intelligent control technology in modern air-conditioning systems. It realizes intelligent adjustment of refrigerant charge by real-time monitoring of ambient temperature, room area and system operating status.

[0168] When the air conditioner is running, the system calculates the cooling demand of the refrigerant and adjusts the refrigerant charge. By adjusting the refrigerant pressure and flow, it can reduce the wear of pipeline components and the resulting refrigerant gas leakage.

[0169] The specific implementation of the patent of this invention is that after detecting a refrigerant leak and issuing an early warning, all the data of the entire period of use of the air-conditioning system (data from each sensor, data generated by the algorithm, and system user setting data) are saved, and the data is combined with the refrigerant filling quantity management. When the system detects or predicts the same data next time, the refrigerant filling quantity can be dynamically adjusted in advance to reduce the refrigerant gas pressure in the pipeline to avoid the copper pipe welding points in the pipeline from being damaged due to excessive pressure and leaking refrigerant gas. The core point is to effectively avoid leakage by combining the data after the leakage warning with the dynamic refrigerant filling quantity control.

[0170] The specific refrigerant leakage detection and control method provided in the embodiment of the present application adds a micro gas analyzer to the gaseous refrigerant discharge port of the compressor to detect the gas composition, and sends it to the main chip (MCU) for identification. The main chip adjusts the control mode after identification. Improve the universality of the system. The detection module adopts dual-end detection of the indoor unit main board and the outdoor unit main board. The indoor unit main board monitors the refrigerant concentration and the ambient temperature and humidity in real time. The outdoor unit main board mainly monitors the operating parameters, current, and pressure fluctuations of the compressor. Comprehensive analysis of data improves detection accuracy. The main chip determines the degree of leakage based on the monitored data, and the ultrasonic sensor locates the leakage point and makes corresponding controls. By combining this control method with user usage habits, a dynamic optimization refrigerant filling strategy is used to reduce pipeline pressure shock, which can effectively avoid refrigerant leakage.

[0171] Based on the same inventive concept, Figure 5 As shown, the present application also provides a refrigerant leakage detection and control device 50, comprising:

[0172] The sensor data acquisition module 51 is used to acquire data from multiple sensors, wherein the multiple sensors include at least a pressure sensor, a temperature sensor, and a gas concentration sensor;

[0173] Among them, the pressure sensor is used to obtain the system pressure, such as the system high pressure;

[0174] The temperature sensor is used to obtain the surface temperature of the heat exchanger, such as the surface temperature of the evaporator and / or condenser;

[0175] The gas concentration sensor is used to obtain the concentration of leaked gas.

[0176] In addition, it can also include ultrasonic sensors, compressor current sampling sensors, infrared sensors, and temperature and humidity sensors.

[0177] The installation position of each sensor is set according to actual needs.

[0178] In order to reduce interference, the embodiment of the present application installs the sensor on a shock-proof sensor bracket to avoid false detection or detection fluctuations caused by vibration.

[0179] The target parameter acquisition module 52 is used to pre-process the sensor data to obtain target parameters, which include: leakage gas concentration, system pressure, and heat exchanger surface temperature.

[0180] It should be noted that the data obtained by the sensor is an analog signal, which needs to be converted into a digital signal by a digital-to-analog conversion module and then filtered and calibrated.

[0181] In practice, the value obtained after the above operation is not accurate, which seriously affects the detection effect. Therefore, as a preferred implementation method of the present application, the measurement value at the current moment is determined based on the measurement value determined at the previous moment and the data obtained at the current moment; the details are as follows:

[0182] Current moment measurement value = previous moment measurement value * (1-preset weight coefficient) + preset weight coefficient * current moment acquisition data.

[0183] The preset weight coefficient is a positive number less than 1 and is set according to actual needs.

[0184] After the above processing, the obtained measured value is closer to the true value and can effectively provide a control effect.

[0185] In addition, in order to obtain more accurate target parameters, this application also includes:

[0186] Setting the initial state estimate and the initial error covariance matrix P0; define the state transfer matrix A, the control input matrix B, the observation matrix H, the process noise covariance matrix Q and the observation noise covariance matrix R;

[0187] For each time step k, predict the state and error covariance matrix at the next moment:

[0188]

[0189] P k|k-1 =AP k-1|k-1 A T +Q

[0190] in, is the state prediction estimate for the kth time step based on the information of the k-1th time step, is the state update estimate of the k-1th time step based on the information of the k-1th time step, u k is the control input vector; P k|k-1 is the prediction error covariance matrix of the kth time step based on the information of the k-1th time step; P k-1|k-1 is the updated error covariance matrix of the k-1th time step obtained based on the information of the k-1th time step;

[0191] Update each measurement value and update the measurement values ​​of multiple sensors and P k|k :

[0192] K k =P k|k-1 H T (HP k|k-1 H T+R) -1

[0193]

[0194] P k|k =(IK k H)P k|k-1

[0195] Among them, K k is the gain at the kth time step, Z k is the measurement value at the kth time step, which can be the measurement value calculated after the preset weight coefficient, or the measurement value obtained directly from the sensor. is the updated state estimate of the kth time step based on the information of the kth time step, P k|k The updated error covariance matrix of the kth time step is obtained based on the information of the kth time step, where I is the identity matrix;

[0196] Will as the target parameter at the kth time step.

[0197] That is, the present application solution can effectively reduce the noise and interference of the sensor measurement value through the above algorithm, ensuring that the target parameter finally obtained can truly represent the real value.

[0198] a control strategy determination module 53, configured to determine a target control strategy based on the target parameter when the leakage gas concentration is greater than a preset concentration;

[0199] When the concentration of leaked gas is greater than the preset concentration, there is a risk of explosion, so further control is required.

[0200] Specifically, when the concentration of the leaked gas is greater than a preset concentration, the leakage time during which the concentration of the leaked gas is greater than the preset concentration is obtained, and the pressure difference between the system pressure and the calibration pressure is calculated, and the temperature difference between the surface temperature of the heat exchanger and the theoretical temperature is calculated;

[0201] A target control strategy is determined based on the leakage duration, the pressure difference, and the temperature difference range.

[0202] Exemplarily, determining a target control strategy based on the leakage duration, the pressure difference, and the temperature difference range includes:

[0203] When the leakage duration is less than or equal to a first preset duration, the pressure differential is less than or equal to a first preset pressure differential, and the temperature differential is less than or equal to a first preset pressure differential, the target control strategy is determined to be the first control strategy. The first control strategy includes at least one of the following: sending an alarm and obtaining the leak location. In other words, the first control strategy is only adopted when all three conditions are met. In this case, the leakage is not serious and can likely be resolved by the user. This eliminates the need to disconnect the power supply or shut down the compressor, thus ensuring system uptime while ensuring operational safety and improving the user experience.

[0204] When the leakage duration is greater than the first preset duration and less than the second preset duration, or the pressure difference is greater than the first preset pressure difference and less than the second preset pressure difference, or the temperature difference is greater than the first preset pressure difference and less than the second preset pressure difference, the target control strategy is determined to be the second control strategy, and the second control strategy includes at least one of the following: shutting down the compressor, starting emergency ventilation, and sending a maintenance notification; that is, when one of the above three conditions is met, the second control strategy is adopted.

[0205] If the leakage duration is greater than or equal to the second preset duration, or the pressure difference is greater than or equal to the second preset pressure difference, or the temperature difference is greater than or equal to the second preset pressure difference, the target control strategy is determined to be a third control strategy. The third control strategy includes at least one of the following: emergency shutdown and remote alarm. That is, the third control strategy is adopted when one of the above three conditions is met.

[0206] It is understood that the determination conditions of the third control strategy have the highest priority. For example, if the pressure difference is greater than the first preset pressure difference and less than the second preset pressure difference, and the temperature difference is greater than the first preset pressure difference and less than the second preset pressure difference, but the leakage duration is greater than or equal to the second preset duration, the third control strategy will be adopted. Although two of the conditions of the second control strategy are met, the third control strategy will be adopted first because its determination conditions have the highest priority. Only after it is determined that the third control strategy is not met will the second control strategy be determined.

[0207] Alternatively, while ensuring safety, it can ensure system uptime and improve user experience.

[0208] When the leakage duration is greater than or equal to the second preset duration, or the pressure difference is greater than or equal to the second preset pressure difference, or the temperature difference is greater than or equal to the second preset pressure difference, the target control strategy is determined to be the third control strategy, and the third control strategy includes at least one of the following: emergency shutdown, remote alarm.

[0209] In other cases, a second control strategy is determined, and the second control strategy includes at least one of the following: shutting down the compressor, starting emergency ventilation, and sending a maintenance notice.

[0210] It should be noted that it also includes:

[0211] Acquire sound waves based on ultrasonic sensors;

[0212] When the sound wave is determined to be generated by refrigerant leakage based on the frequency of the sound wave, the leakage location is determined based on data from at least three ultrasonic sensors, where the data from the ultrasonic sensors include: the earliest reception time of the same sound wave and the location of each ultrasonic sensor.

[0213] In addition, it should be noted that different refrigerant types have different preset concentrations.

[0214] In order to achieve more unified control, in one embodiment of the present application, a micro gas analyzer is added to the gaseous refrigerant discharge port of the compressor to detect gas composition, and then a preset concentration is determined based on other components, facilitating personalized control of different refrigerant types.

[0215] The refrigerant leakage control module 54 is configured to perform control based on the target control strategy.

[0216] Additionally, it includes:

[0217] When the concentration of the leaked gas is greater than a preset concentration, determining a target historical moment with the same target parameters as the current target parameters in the historical moments;

[0218] Obtaining control parameters of the target historical moment, the control parameters including a target refrigerant charge amount;

[0219] Control is performed based on the control parameters.

[0220] For example, after a refrigerant leak is detected and an early warning is issued, all data from the entire period of use of the air conditioning system (sensor data, data generated by the algorithm, and system user settings) is saved and combined with refrigerant charge management. When the system detects or predicts the same data next time, it can proactively adjust the refrigerant charge to reduce the refrigerant gas pressure in the pipeline to prevent the copper pipe welding points from being damaged due to excessive pressure and refrigerant gas leakage. The key point is to combine the data after the leak warning with dynamic refrigerant charge control to effectively prevent leaks.

[0221] The refrigerant leakage detection and control device provided in the embodiment of the present application stores executable instructions of the processor in a memory. When the executable instructions are executed, the processor can, after acquiring multi-channel sensor data, pre-process the sensor data to obtain target parameters. When the concentration of the leaked gas is greater than a preset concentration, the processor determines a target control strategy based on the target parameters, and finally performs control based on the target control strategy. The present application scheme pre-processes the sensor data instead of using it directly, which can make the measurement results more accurate, and thus can accurately determine whether the refrigerant has leaked. In addition, after the refrigerant leaks, the corresponding control method can be adopted according to the target parameters. In different situations, appropriate control strategies can be adopted to effectively deal with potential dangers caused by the leak.

[0222] Based on the same inventive concept, Figure 6 As shown, the present application also provides a refrigerant leakage detection and control system 60, comprising:

[0223] at least one processor 61 and at least one memory 62;

[0224] The memory stores executable instructions of the processor;

[0225] The processor is configured to execute the refrigerant leakage detection and control method provided in the above embodiment.

[0226] The refrigerant leakage detection and control system provided by the embodiment of the present application stores executable instructions of the processor in a memory. When the executable instructions are executed, the processor can, after acquiring multi-channel sensor data, pre-process the sensor data to obtain target parameters. When the concentration of the leaked gas is greater than a preset concentration, the processor determines a target control strategy based on the target parameters, and finally performs control based on the target control strategy. The present application scheme pre-processes the sensor data instead of using it directly, which can make the measurement results more accurate, and thus can accurately determine whether the refrigerant has leaked. In addition, after the refrigerant leaks, the corresponding control method can be adopted according to the target parameters. In different situations, appropriate control strategies can be adopted to effectively deal with potential dangers caused by the leak.

[0227] Based on the same inventive concept, the present application provides an air conditioner, which applies the refrigerant leakage detection and control method provided in the above embodiment.

[0228] The air conditioner provided by the present application scheme, by applying the refrigerant leak detection and control method provided by the above-mentioned embodiment, can, after acquiring multi-channel sensor data, pre-process the sensor data to obtain target parameters. When the leaked gas concentration is greater than a preset concentration, a target control strategy is determined based on the target parameters, and finally control is performed based on the target control strategy. The present application scheme pre-processes the sensor data rather than directly using it, which can make the measurement results more accurate, and thus accurately determine whether the refrigerant has leaked. In addition, after a refrigerant leak occurs, a corresponding control method can be adopted based on the target parameters. In different situations, appropriate control strategies can be adopted to effectively address potential dangers caused by the leak.

[0229] It should be noted that, in the description of this application, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0230] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

Claims

1. A refrigerant leakage detection and control method, characterized in that: include: Acquire data from multiple sensors, wherein the multiple sensors include at least a pressure sensor, a temperature sensor, and a gas concentration sensor; Preprocessing the sensor data to obtain target parameters, the target parameters including: leakage gas concentration, system pressure, and heat exchanger surface temperature; When the leakage gas concentration is greater than a preset concentration, determining a target control strategy based on the target parameter; Control is performed based on the target control strategy.

2. The method according to claim 1, wherein: The preprocessing of the sensor data to obtain target parameters includes: Get the analog signal collected by the sensor; Convert the analog signals into digital signals, and perform filtering and calibration; Determine the current moment's measurement value based on the measurement value determined at the previous moment and the data acquired at the current moment; current moment's measurement value = previous moment's measurement value * (1 - preset weight coefficient) + preset weight coefficient * current moment's acquired data; A target parameter is obtained based on the measured values.

3. The method according to claim 1, wherein: The preprocessing of the sensor data to obtain target parameters includes: Set the initial state estimate x0 and the initial error covariance matrix P0; define the state transfer matrix A, the control input matrix B, the observation matrix H, the process noise covariance matrix Q and the observation noise covariance matrix R; For each time step k, predict the state and error covariance matrix at the next moment: P k|k-1 =AP k-1|k-1 From T +Q in, is the state prediction estimate for the kth time step based on the information of the k-1th time step, is the state update estimate of the k-1th time step based on the information of the k-1th time step, u k is the control input vector; P k|k-1 is the prediction error covariance matrix of the kth time step based on the information of the k-1th time step; P k-1|k-1 is the updated error covariance matrix of the k-1th time step obtained based on the information of the k-1th time step; Update each measurement value and update the measurement values ​​of multiple sensors and P k|k : K k =P k|k-1 H T (HP k|k-1 H T +R) -1 P k|k =(I-K k H)P k|k-1 Among them, K k is the gain at the kth time step, Z k is the measurement value at the kth time step, is the updated state estimate of the kth time step based on the information of the kth time step, P k|k The updated error covariance matrix of the kth time step is obtained based on the information of the kth time step, where I is the identity matrix; Will as the target parameter at the kth time step.

4. The method according to claim 1, wherein: When the leakage gas concentration is greater than a preset concentration, determining a target control strategy based on the target parameter includes: When the concentration of the leaked gas is greater than a preset concentration, the leakage duration during which the concentration of the leaked gas is greater than the preset concentration is obtained, and the pressure difference between the system pressure and the calibration pressure is calculated, as well as the temperature difference between the surface temperature of the heat exchanger and the theoretical temperature is calculated; A target control strategy is determined based on the leakage duration, the pressure difference, and the temperature difference range.

5. The method according to claim 4, characterized in that: The determining of the target control strategy based on the leakage duration, the pressure difference, and the temperature difference range includes: When the leakage duration is less than or equal to a first preset duration, the pressure difference is less than or equal to a first preset pressure difference, and the temperature difference is less than or equal to the first preset pressure difference, determining that the target control strategy is at least one of the following: sending an alarm, obtaining a leakage location; When the leakage duration is greater than a first preset duration and less than a second preset duration, or the pressure difference is greater than a first preset pressure difference and less than a second preset pressure difference, or the temperature difference is greater than the first preset pressure difference and less than the second preset pressure difference, determining the target control strategy to be at least one of the following: shutting down the compressor, starting emergency ventilation, and sending a maintenance notice; When the leakage duration is greater than or equal to the second preset duration, or the pressure difference is greater than or equal to the second preset pressure difference, or the temperature difference is greater than or equal to the second preset pressure difference, the target control strategy is determined to be at least one of the following: emergency shutdown, remote alarm.

6. The method according to claim 1, characterized in that Also includes: Acquire sound waves based on ultrasonic sensors; When the sound wave is determined to be generated by refrigerant leakage based on the frequency of the sound wave, the leakage location is determined based on data from at least three ultrasonic sensors, where the data from the ultrasonic sensors include: the earliest reception time of the same sound wave and the location of each ultrasonic sensor.

7. The method according to claim 1, characterized in that Also includes: When the concentration of the leaked gas is greater than a preset concentration, determining a target historical moment with the same target parameters as the current target parameters in the historical moments; Obtaining control parameters of the target historical moment, the control parameters including a target refrigerant charge amount; Control is performed based on the control parameters.

8. A refrigerant leakage detection and control device, characterized in that: include: A sensor data acquisition module is used to acquire data from multiple sensors, wherein the multiple sensors include at least a pressure sensor, a temperature sensor, and a gas concentration sensor; A target parameter acquisition module is used to pre-process the sensor data to obtain target parameters, wherein the target parameters include: leakage gas concentration, system pressure, and heat exchanger surface temperature; a control strategy determination module, configured to determine a target control strategy based on the target parameter when the leakage gas concentration is greater than a preset concentration; The refrigerant leakage control module is used to perform control based on the target control strategy.

9. A refrigerant leakage detection and control system, characterized in that: include: at least one processor and at least one memory; The memory stores executable instructions of the processor; The processor is configured to execute the method according to any one of claims 1 to 7.

10. An air conditioner, characterized in that: The method according to any one of claims 1 to 7 is used.

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