TWI722617B - System and method for a non-intrusive refrigerant leakage detection and adaptive method for threshold thereof - Google Patents
System and method for a non-intrusive refrigerant leakage detection and adaptive method for threshold thereof Download PDFInfo
- Publication number
- TWI722617B TWI722617B TW108138517A TW108138517A TWI722617B TW I722617 B TWI722617 B TW I722617B TW 108138517 A TW108138517 A TW 108138517A TW 108138517 A TW108138517 A TW 108138517A TW I722617 B TWI722617 B TW I722617B
- Authority
- TW
- Taiwan
- Prior art keywords
- historical
- threshold value
- equipment
- refrigerant leakage
- value
- Prior art date
Links
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D29/00—Arrangement or mounting of control or safety devices
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D2600/00—Control issues
- F25D2600/02—Timing
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D2600/00—Control issues
- F25D2600/06—Controlling according to a predetermined profile
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Physics & Mathematics (AREA)
- Mechanical Engineering (AREA)
- Thermal Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Cold Air Circulating Systems And Constructional Details In Refrigerators (AREA)
- Defrosting Systems (AREA)
- Examining Or Testing Airtightness (AREA)
Abstract
Description
本揭露係關於冷媒洩漏偵測技術，詳而言之，係關於一種非侵入式冷媒洩漏偵測系統、其方法以及其門檻值自適化之方法。This disclosure is about refrigerant leakage detection technology. In detail, it is about a non-intrusive refrigerant leakage detection system, its method, and its threshold self-adjustment method.
因應全球暖化以及臭氧層破壞等環境意識提升，製冷系統的冷媒開始以碳氫化合物和混合冷媒取代會造成嚴重溫室效應的碳氫氟化合物，由於冷媒具有***性和毒性，因而冷媒洩漏不僅會令製冷系統運轉效率下降，對人體也會產生不利影響及危險。In response to increased environmental awareness such as global warming and the destruction of the ozone layer, the refrigerant in the refrigeration system has begun to replace hydrocarbons and mixed refrigerants that can cause serious greenhouse effect. Because the refrigerant is explosive and toxic, refrigerant leakage will not only cause refrigeration The reduction in system operating efficiency will also have adverse effects and dangers on the human body.
再者，冷凍冷藏櫃的製冷系統占超市的能耗超過50%，從節能和經濟效益來看，製冷系統穩運轉效率是非常重要的，此外為了食安問題，若發現冷凍冷藏櫃未能保持在正確的溫度時，必須銷毀櫃內食品，意味著食品的浪費和庫存成本提升，因此，監測製冷的系統不僅是監測櫃內溫度，更須能夠提早感測出冷凍冷藏櫃即將出現故障之預警功能，才能讓監測達到最大功效。惟目前檢測冷凍冷藏櫃運轉異常之系統有幾個缺失：1、僅有警報功能，故仍需維修師傅到場檢修，處理時間長且浪費人力資源；2、系統故障異常訊息不足，無法提供有效的故障問題點，店員無法即時提供資訊給維修師傅；3、感測器種類和數量均不足，亦即成本考量下，多數冷凍冷藏櫃僅有出風和蒸發器溫度計等感測器。In addition, the refrigeration system of the freezer and refrigerator accounts for more than 50% of the energy consumption of the supermarket. From the perspective of energy saving and economic benefits, the stable operation efficiency of the refrigeration system is very important. In addition, for food safety problems, if the freezer and refrigerator fail to maintain At the correct temperature, the food in the cabinet must be destroyed, which means food waste and increased inventory costs. Therefore, the monitoring system for refrigeration is not only to monitor the temperature in the cabinet, but also to be able to detect the early warning of the imminent failure of the freezer and refrigerator. Function, so that the monitoring can reach the maximum effect. However, the current system for detecting abnormal operation of refrigerated cabinets has several shortcomings: 1. There is only an alarm function, so a maintenance master still needs to be on-site for maintenance, which takes a long time and wastes human resources; 2. There is insufficient information about system failures and abnormalities to provide effective The clerk cannot provide information to the maintenance technician in real time; 3. The types and quantities of sensors are insufficient, that is, due to cost considerations, most refrigerating cabinets only have sensors such as air outlet and evaporator thermometers.
此外，依據超商的冷凍冷藏櫃之維修資料分析，冷媒洩漏占限時維修中約10%，若可提前預知冷媒洩漏，將可大幅度降低食物損壞的風險和維修人員的人力成本，從限時維修降為一般維修保養。惟現行多數冷媒洩漏偵測方式是額外增加感測器或是連接壓縮機，不僅會增加硬體成本，且在運作中的冷凍冷藏櫃上安裝上非常困難，因施工成本高而推廣不易。In addition, according to the analysis of the maintenance data of the refrigerator and refrigerator of the supermarket, the refrigerant leakage accounts for about 10% of the time-limited maintenance. If the refrigerant leakage can be predicted in advance, the risk of food damage and the labor cost of the maintenance personnel will be greatly reduced. Reduce to general maintenance. However, most of the current refrigerant leakage detection methods are to add additional sensors or connect the compressor, which not only increases the hardware cost, but also is very difficult to install on the operating freezer and refrigerator, and it is not easy to promote because of the high construction cost.
因此，如何能在不需額外硬體成本和施工成本下，在冷凍冷藏櫃中增加冷媒洩漏預警功能，此將成為本技術領域人員極欲解決的課題。Therefore, how to add a refrigerant leakage warning function to the refrigerating and refrigerating cabinet without additional hardware costs and construction costs will become a subject that those skilled in the art want to solve.
有鑑於此，本揭露提供一種非侵入式冷媒洩漏偵測技術，利用既有溫度感測器，並結合運作模式與設備歷史資料之分析，藉以解決上述技術問題。In view of this, the present disclosure provides a non-intrusive refrigerant leakage detection technology that uses existing temperature sensors, combined with analysis of operating modes and equipment history data, to solve the above technical problems.
本揭露提供一種非侵入式冷媒洩漏偵測方法，係包括：取得冷凍冷藏櫃之運作模式輸出值，及取得位於該冷凍冷藏櫃內之溫度感測器所感測之溫度值；利用該運作模式輸出值取得該冷凍冷藏櫃之除霜間隔時間，以一個除霜間隔時間作為一時窗，藉此計算每一時窗內該溫度值之平均溫度值以及該每一時窗內該平均溫度值的變異數；透過設備歷史資料取得建議門檻值；以及計算該平均溫度值的變異數與該建議門檻值之比值，以於該比值大於1時，判斷為冷媒洩漏之狀況。 The present disclosure provides a non-intrusive refrigerant leakage detection method, which includes: obtaining the output value of the operation mode of the refrigerating cabinet, and obtaining the temperature value sensed by the temperature sensor located in the refrigerating cabinet; using the operation mode to output The value obtains the defrost interval time of the refrigerating cabinet, and uses a defrost interval time as a time window to calculate the average temperature value of the temperature value in each time window and the variance of the average temperature value in each time window; Obtain the recommended threshold value through the equipment history data; and calculate the ratio of the variance of the average temperature value to the recommended threshold value, so that when the ratio is greater than 1, it is judged as a refrigerant leakage condition.
本揭露提供一種非侵入式冷媒洩漏偵測系統，其包括：資料收集模組，用於取得冷凍冷藏櫃之運作模式輸出值以及位於該冷凍冷藏櫃內之溫度感測器所感測之溫度值；計算模組，用於利用該運作模式輸出值取得該冷凍冷藏櫃之除霜間隔時間，以一個除霜間隔時間作為一時窗，藉此計算每一時窗內該溫度值之平均溫度值以及該每一時窗內該平均溫度值的變異數；門檻值模組，用於透過設備歷史資料取得建議門檻值；以及判斷模組，用於計算該平均溫度值的變異數與該建議門檻值之比值，以於該比值大於1時，判斷有冷媒洩漏之狀況。 The present disclosure provides a non-intrusive refrigerant leakage detection system, which includes: a data collection module for obtaining the output value of the operation mode of the refrigerating cabinet and the temperature value sensed by a temperature sensor located in the refrigerating cabinet; The calculation module is used to obtain the defrost interval time of the refrigerating cabinet using the output value of the operation mode, and use a defrost interval time as a time window to calculate the average temperature value of the temperature value in each time window and each time window. The variance of the average temperature within a time window; the threshold module, which is used to obtain the recommended threshold value through the historical data of the equipment; and the judgment module, which is used to calculate the ratio of the variance of the average temperature to the recommended threshold, When the ratio is greater than 1, it is judged that there is a refrigerant leakage.
本揭露提供門檻值自適化之方法，係應用於非侵入式冷媒洩漏偵測系統，該方法包括：取得冷凍冷藏櫃之歷史維修紀錄以及設備歷史資料；依據該設備歷史資料計算出該冷凍冷藏櫃之設備歷史變異數；計算該設備歷史變異數與預設之初始門檻值之歷史比值，俾依據該歷史比值判斷冷媒狀態以得到預測結果；比對該預測結果與該歷史維修紀錄，藉以判定該初始門檻值之準確性；以及依據該準確性調整該初始門檻值而作為該非侵入式冷媒洩漏偵測系統判斷冷媒洩漏之門檻值。This disclosure provides a threshold value self-adjustment method, which is applied to a non-invasive refrigerant leakage detection system. The method includes: obtaining historical maintenance records and equipment history data of the refrigerated refrigerated cabinet; calculating the refrigerated refrigerated cabinet based on the historical data of the equipment The historical variance of the equipment; calculate the historical ratio of the historical variance of the equipment to the preset initial threshold to determine the state of the refrigerant based on the historical ratio to obtain the predicted result; compare the predicted result with the historical maintenance record to determine the The accuracy of the initial threshold; and adjusting the initial threshold according to the accuracy as the threshold for the non-intrusive refrigerant leakage detection system to determine refrigerant leakage.
綜上可知，本揭露為一種非侵入式冷媒洩漏偵測系統、其方法以及其門檻值自適化之方法，基於常見之冷凍冷藏系統其溫控器皆具有出風口及/或蒸發器之溫度感測器，因而本揭露僅利用出風口或蒸發器之溫度感測器所感測溫度以及冷凍冷藏櫃之運轉模式，收集冷凍冷藏櫃之設備歷史資料，透過自主學習，計算出變異數、平均值和門檻值，並利用變異數和自適化門檻值關係判斷故障狀態，如此在無須增加額外成本下，能以現有設備及冷媒洩漏偵測演算法推測出冷媒洩漏狀態，並能即時告警使用者以進行維修。In summary, this disclosure is a non-intrusive refrigerant leakage detection system, its method, and its threshold value self-adjusting method. Based on the common refrigeration system, the temperature controller has the temperature sense of the air outlet and/or evaporator. Therefore, this disclosure uses only the temperature sensed by the temperature sensor of the air outlet or evaporator and the operation mode of the freezer-refrigerator to collect the equipment history data of the freezer-refrigerator, and calculate the variance, average value and Threshold value, and use the relationship between the variance and the adaptive threshold value to determine the fault status, so that without additional costs, the refrigerant leakage status can be inferred with the existing equipment and refrigerant leakage detection algorithm, and the user can be alerted immediately to proceed. service.
以下藉由特定的具體實施形態說明本揭露之技術內容，熟悉此技藝之人士可由本說明書所揭示之內容輕易地瞭解本揭露之優點與功效。然本揭露亦可藉由其他不同的具體實施形態加以施行或應用。The following describes the technical content of the present disclosure through specific specific implementation forms, and those familiar with this technique can easily understand the advantages and effects of the present disclosure from the content disclosed in this manual. However, the present disclosure can also be implemented or applied in other different specific embodiments.
第1圖為本揭露之非侵入式冷媒洩漏偵測方法的步驟圖。本揭露所述非侵入式冷媒洩漏偵測方法其目的用於偵測冷媒是否洩漏，由於冷媒流量會影響製冷效果，在本揭露冷媒洩漏偵測方法中，於冷凍冷藏櫃中安裝溫度感測器並取得其運轉模式，透過收集資料並分析其歷史數據以偵測冷媒洩漏之故障，亦即利用歷史紀錄資料產生門檻值，且透過計算每一期間平均溫度值和變異數，藉由判斷變異數與門檻值之比值，以作為判斷冷媒是否洩漏之依據。Figure 1 is a step diagram of the disclosed non-invasive refrigerant leakage detection method. The non-invasive refrigerant leakage detection method of the present disclosure is used to detect whether the refrigerant is leaking. Since the flow of the refrigerant will affect the refrigeration effect, in the refrigerant leakage detection method of the present disclosure, a temperature sensor is installed in the refrigerating cabinet And obtain its operating mode, collect data and analyze its historical data to detect the failure of refrigerant leakage, that is, use historical record data to generate threshold values, and by calculating the average temperature value and variance of each period, by judging the variance The ratio to the threshold value is used as the basis for judging whether the refrigerant is leaking.
於步驟S11，取得冷凍冷藏櫃之運作模式輸出值。於此步驟中，係取得該冷凍冷藏櫃其運作模式輸出值，運作模式輸出值包括該冷凍冷藏櫃運轉時處於非除霜時間(冷藏時間)或除霜時間。In step S11, the output value of the operation mode of the freezer-refrigerator is obtained. In this step, the output value of the operation mode of the refrigerator-freezer is obtained, and the output value of the operation mode includes the non-defrosting time (refrigerating time) or the defrosting time of the refrigerator-freezer during operation.
於步驟S12，取得位於該冷凍冷藏櫃內之溫度感測器所感測之溫度值。於此步驟中，係取得該冷凍冷藏櫃中溫度感測器所感測之溫度值，本揭露是透過判斷該冷凍冷藏櫃內出風口溫度狀態，進而透過與設備歷史資料相比較，進而推判冷媒是否有洩漏情況，惟溫度感測器並非限制僅能在出風口，舉例來說，該溫度感測器可為出風口溫度感測器或蒸發器溫度感測器。In step S12, the temperature value sensed by the temperature sensor located in the refrigerating cabinet is obtained. In this step, the temperature value sensed by the temperature sensor in the freezer-refrigerator is obtained. This disclosure is to determine the temperature state of the air outlet in the freezer-refrigerator, and then compare with the historical data of the equipment to determine the refrigerant Whether there is a leak, but the temperature sensor is not limited to only at the air outlet. For example, the temperature sensor can be an air outlet temperature sensor or an evaporator temperature sensor.
於步驟S13，利用該運作模式輸出值取得該冷凍冷藏櫃之除霜間隔時間，以一個除霜間隔時間作為一時窗，藉此計算每一時窗內該溫度值之平均溫度值以及該每一時窗內該平均溫度值的變異數。於此步驟中，由該運作模式輸出值取得該冷凍冷藏櫃之除霜間隔時間，並將一個除霜間隔時間設定為一個時窗，並計算每一時窗內該溫度值之平均溫度值，更具體來說，所謂除霜間隔時間是指本次開始除霜到下一次開始除霜的整個期間，其中包含了本次的除霜時間及除霜完畢後的非除霜時間，而計算平均溫度值是將非除霜時間的溫度值進行加總平均，接著再將每一時窗內的該平均溫度值計算變異數。In step S13, use the output value of the operation mode to obtain the defrost interval time of the refrigerating cabinet, and use a defrost interval time as a time window to calculate the average temperature value of the temperature value in each time window and each time window The variance of the average temperature value within. In this step, the defrost interval time of the refrigerating cabinet is obtained from the output value of the operation mode, and a defrost interval time is set as a time window, and the average temperature value of the temperature value in each time window is calculated. Specifically, the so-called defrost interval refers to the entire period from the current defrost to the next defrost, which includes the current defrost time and the non-defrost time after the defrost is completed, and the average temperature is calculated The value is to add and average the temperature values of the non-defrost time, and then calculate the variance of the average temperature value in each time window.
於步驟S14，透過設備歷史資料取得建議門檻值。此步驟係說明可依據該冷凍冷藏櫃之設備歷史資料，進而取得由該設備歷史資料所得到之建議門檻值，此建議門檻值用於提供判斷冷媒洩漏與否。In step S14, the recommended threshold value is obtained through the device history data. This step means that the recommended threshold value obtained from the historical data of the equipment can be obtained based on the equipment history data of the refrigerating cabinet. The recommended threshold value is used to determine whether the refrigerant leaks or not.
於一實施例中，此建議門檻值一開始可為一個利用現有的設備歷史資料求得之預設值，後續可透過自適化調整門檻值設定(adaptive thresholding)，關於自適化後續將再詳述。In one embodiment, the suggested threshold value can be a preset value obtained by using the existing equipment history data at the beginning, and the threshold value setting can be adjusted through self-adjustment (adaptive thresholding). The self-adjustment will be described in detail later .
於步驟S15，計算該平均溫度值的變異數與該建議門檻值之比值，以於該比值大於1時，判斷為冷媒洩漏之狀況。於此步驟中，是透過該平均溫度值的變異數與該建議門檻值之比值作為判斷冷媒洩漏之依據，亦即將該平均溫度值的變異數除以該建議門檻值，當比值大於1時，則判斷冷媒洩漏，反之，當該比值不大於1時，則判斷為冷媒正常之狀況，即設備冷媒情況正常，無洩漏。In step S15, the ratio of the variance of the average temperature value to the recommended threshold is calculated, so that when the ratio is greater than 1, it is judged as a refrigerant leakage condition. In this step, the ratio of the variance of the average temperature value to the recommended threshold is used as the basis for judging refrigerant leakage, that is, the variance of the average temperature value is divided by the recommended threshold. When the ratio is greater than 1, It is judged that the refrigerant is leaking. On the contrary, when the ratio is not greater than 1, it is judged that the refrigerant is normal, that is, the condition of the equipment refrigerant is normal and there is no leakage.
如前所述，本揭露所述方法中，透過該設備歷史資料取得該建議門檻值係包括於每隔一預設時間依據歷史紀錄比較結果自適化調整該建議門檻值，有關自適化調整該建議門檻值可透過程序進行，包括：取得該冷凍冷藏櫃之歷史維修紀錄以及該設備歷史資料；依據該設備歷史資料計算出該冷凍冷藏櫃之設備歷史變異數；計算該設備歷史變異數與預設之初始門檻值之歷史比值，俾依據該歷史比值判斷冷媒狀態以得到預測結果；比對該預測結果與該歷史維修紀錄，藉以判定該初始門檻值之準確性；以及依據該準確性調整該初始門檻值而作為該非侵入式冷媒洩漏偵測系統判斷冷媒洩漏之門檻值。As mentioned above, in the method described in this disclosure, obtaining the recommended threshold value through the historical data of the device includes automatically adjusting the recommended threshold value according to the comparison result of the historical records at a predetermined time interval, and adjusting the suggestion in relation to the automatic adaptation. The threshold value can be carried out through procedures, including: obtaining the historical maintenance record of the refrigerating cabinet and the historical data of the equipment; calculating the historical variance of the refrigerating cabinet based on the historical data of the equipment; calculating the historical variance of the equipment and the preset The historical ratio of the initial threshold to determine the state of the refrigerant based on the historical ratio to obtain the predicted result; compare the predicted result with the historical maintenance record to determine the accuracy of the initial threshold; and adjust the initial threshold based on the accuracy The threshold value is used as the threshold value for the non-intrusive refrigerant leakage detection system to determine refrigerant leakage.
易言之，由設備歷史資料中同樣取得每一個時窗的歷史變異數，並進行該設備歷史變異數與預設之初始門檻值之歷史比值的計算，如此同樣會得到冷媒洩漏和設備正常的預測結果，將此預測結果與實際的維修紀錄(無論有無維修)進行比對，若預測結果與實際的維修紀錄則表示初始門檻值是適用的，此初始門檻值將可成為建議門檻值。另外，隨著該冷凍冷藏櫃持續監測，新增加的設備歷史資料將可成為後續建議門檻值是否適用的判斷依據，故可於每隔一段時間，例如1個月，進行門檻值檢測，看是否需要調整建議門檻值，此即是門檻值自適化。In other words, the historical variance of each time window is also obtained from the historical data of the equipment, and the historical ratio of the historical variance of the equipment to the preset initial threshold is calculated, so that the refrigerant leakage and normal equipment will also be obtained. Forecast results, compare the forecast results with actual maintenance records (with or without maintenance). If the forecast results and actual maintenance records indicate that the initial threshold is applicable, this initial threshold will become the recommended threshold. In addition, with the continuous monitoring of the freezer-refrigerator, the newly added equipment history data will be the basis for judging whether the subsequent recommended threshold value is applicable, so the threshold value can be tested at regular intervals, such as 1 month, to see if The recommended threshold value needs to be adjusted, which is the threshold value self-adjustment.
第2圖為本揭露一實施例之非侵入式冷媒洩漏偵測方法的流程圖。如圖所示，偵測開始後，會先取得溫度感測器的資料，也就是溫度值，同時也會取得冷凍冷藏櫃運轉模式輸出值，亦即何時冷凍/冷藏狀態，何時進行除霜，由於這些數值(溫度值、運轉模式輸出值)都來自冷凍冷藏櫃某些元件上，例如溫度感測器以及運轉模式紀錄器，故會將這些數值先送至資料收集接收器，例如冷凍冷藏櫃所設置的一個接收器，接著由該資料收集接收器將溫度值、運轉模式輸出值等數值傳送至雲端資料庫進行儲存。雲端資料庫之利用除了可儲存大量資料外，由於須持續進行數值計算與分析，故可透過類似雲端伺服器進行分析計算，也可避免單一設備計算負載過大。FIG. 2 is a flowchart of a non-invasive refrigerant leakage detection method according to an embodiment of the disclosure. As shown in the figure, after the detection starts, the data of the temperature sensor will be obtained first, that is, the temperature value, and the output value of the freezer-refrigerator operation mode will also be obtained, that is, when the freezing/refrigeration status is, and when to defrost. Since these values (temperature value, operation mode output value) come from some components of the freezer-refrigerator, such as temperature sensors and operation mode recorders, these values are first sent to the data collection receiver, such as the freezer-refrigerator A receiver is set, and then the data collection receiver sends the temperature value and the output value of the operation mode to the cloud database for storage. In addition to storing large amounts of data, the use of the cloud database requires continuous numerical calculation and analysis, so it can be analyzed and calculated through a similar cloud server, and it can also avoid a single device's calculation load.
雲端伺服器內可具有一非侵入式冷媒洩漏偵測系統，可用於接收相關數值並進行分析判斷，其中，會先定義出除霜間隔時間為一個時窗，接著計算每一個時窗的平均溫度值以及每一個平均溫度的變異數。另外，從設備歷史資料能取得一個建議門檻值，當平均溫度值的變異數與該建議門檻值的比值大於1時，則判斷冷媒洩漏，反之則表示設備正常。須說明者，該建議門檻值可作自適化的調整，也就是依據後續的設備歷史資料再對該建議門檻值進行準確度的判斷。The cloud server can have a non-intrusive refrigerant leakage detection system, which can be used to receive relevant values and analyze and judge. Among them, the defrost interval is first defined as a time window, and then the average temperature of each time window is calculated Value and the variance of each average temperature. In addition, a recommended threshold value can be obtained from the equipment history data. When the ratio of the variance of the average temperature value to the recommended threshold value is greater than 1, it is judged that the refrigerant is leaking, otherwise, the equipment is normal. It should be noted that the recommended threshold can be adjusted automatically, that is, the accuracy of the recommended threshold can be judged based on subsequent equipment history data.
第3圖為本揭露之門檻值自適化之方法的步驟圖。須說明者，門檻值自適化之方法與非侵入式冷媒洩漏偵測方法並非完全相互影響，也就是說，非侵入式冷媒洩漏偵測方法進行其冷媒洩漏偵測，而門檻值自適化之方法則於一段期間檢測門檻值是否適用，以於門檻值準確度不佳時，調整門檻值，易言之，門檻值自適化之方法可自行執行，需要時才會改變非侵入式冷媒洩漏偵測方法中的建議門檻值。Figure 3 is a step diagram of the threshold self-adjustment method disclosed in this disclosure. It should be noted that the threshold value adaptive method and the non-invasive refrigerant leakage detection method do not completely affect each other, that is, the non-invasive refrigerant leakage detection method performs its refrigerant leakage detection, while the threshold value adaptive method Check whether the threshold value is applicable during a period of time, and adjust the threshold value when the accuracy of the threshold value is not good. In other words, the threshold value self-adjustment method can be implemented by itself, and the non-intrusive refrigerant leakage detection will be changed when needed. The recommended threshold in the method.
於步驟S31中，取得冷凍冷藏櫃之歷史維修紀錄以及設備歷史資料。為了判斷門檻值是否適用，本揭露是採用考量歷史紀錄來做門檻值的調整依據，故於本步驟中，係先取得冷凍冷藏櫃之歷史維修紀錄以及設備歷史資料，歷史維修紀錄包含有無維修紀錄及何時維修，而設備歷史資料即為該冷凍冷藏櫃運轉模式的紀錄。In step S31, the historical maintenance records and equipment historical data of the refrigerating cabinet are obtained. In order to determine whether the threshold value is applicable, this disclosure uses historical records as the basis for adjusting the threshold value. Therefore, in this step, the historical maintenance records and equipment historical data of the refrigerated cabinet are first obtained. The historical maintenance records include whether there are maintenance records. And when to repair, and the equipment history data is the record of the operation mode of the refrigerating cabinet.
於步驟S32中，依據該設備歷史資料計算出該冷凍冷藏櫃之設備歷史變異數。於此步驟中，同樣透過設備歷史資料中的冷凍冷藏櫃運轉模式來計算設備歷史變異數，更具體來說，同樣將設備歷史資料以除霜間隔時間為單位切割成數個時窗，接著計算每一個時窗的平均溫度值，其中，計算平均溫度值時是不納入除霜時間的溫度，接著，再以每一個時窗的平均溫度值計算出每一個時窗的平均溫度值的變異數，這裡稱為歷史變異數。In step S32, the historical variation of the equipment of the refrigerating cabinet is calculated based on the equipment historical data. In this step, the equipment history variation number is also calculated through the operation mode of the refrigerating cabinet in the equipment history data. More specifically, the equipment history data is also cut into several time windows in the unit of defrost interval time, and then each time window is calculated. The average temperature value of a time window, where the temperature is not included in the defrost time when calculating the average temperature value. Then, the average temperature value of each time window is used to calculate the variance of the average temperature value of each time window, This is called the historical variance.
於步驟S33中，計算該設備歷史變異數與預設之初始門檻值之歷史比值，俾依據該歷史比值判斷冷媒狀態以得到預測結果。於此步驟中，同樣判斷變異數與門檻值的比值，具體來說，前一步驟計算出歷史變異數，而這裡可預設初始門檻值，計算該設備歷史變異數與預設之初始門檻值之比值，這裡稱為歷史比值，最後由該歷史比值來判斷冷媒狀態，例如比值大於1為冷媒洩漏，比值未大於1則表示冷媒未洩漏，最後得到一個預測結果。In step S33, the historical ratio of the historical variance of the equipment to the preset initial threshold is calculated, so as to determine the state of the refrigerant based on the historical ratio to obtain the prediction result. In this step, the ratio of the variance to the threshold is also judged. Specifically, the historical variance is calculated in the previous step, and the initial threshold can be preset here to calculate the historical variance of the device and the preset initial threshold The ratio is called the historical ratio here. Finally, the state of the refrigerant is judged by the historical ratio. For example, if the ratio is greater than 1, it means that the refrigerant is leaking, and if the ratio is not greater than 1, it means that the refrigerant has not leaked. Finally, a prediction result is obtained.
於步驟S34中，比對該預測結果與該歷史維修紀錄，藉以判定該初始門檻值之準確性。此步驟係判斷門檻值之準確性，前一步驟已經產生一個預測結果，本步驟將此預測結果與歷史維修紀錄進行比對，假若兩者相符，亦即預測結果推出冷媒可能洩漏，而真實情況的歷史維修紀錄也有維修紀錄，此則表示此門檻值是適用的，反之，若準確度不符合一預設標準，則要進行門檻值調整。In step S34, the prediction result is compared with the historical maintenance record to determine the accuracy of the initial threshold. This step is to judge the accuracy of the threshold value. The previous step has produced a prediction result. This step compares the prediction result with the historical maintenance records. If the two match, the prediction result indicates that the refrigerant may leak, but the real situation The historical maintenance records also have maintenance records, which means that the threshold is applicable. On the contrary, if the accuracy does not meet a preset standard, the threshold must be adjusted.
於步驟S35中，依據該準確性調整該初始門檻值而作為該非侵入式冷媒洩漏偵測系統判斷冷媒洩漏之門檻值。此步驟即依據前一步驟得到的準確性，進行門檻值(該初始門檻值)之調整，調整後的門檻值即為非侵入式冷媒洩漏偵測系統判斷冷媒洩漏之門檻值，也就是第1圖所述方法中的建議門檻值。In step S35, the initial threshold is adjusted according to the accuracy and used as the threshold for the non-intrusive refrigerant leakage detection system to determine refrigerant leakage. This step is to adjust the threshold value (the initial threshold value) based on the accuracy obtained in the previous step. The adjusted threshold value is the threshold value for the non-intrusive refrigerant leakage detection system to determine refrigerant leakage, which is the first The recommended threshold in the method described in the figure.
爾後，可於每隔一段時間下，進行門檻值的自適化調整，同樣採用新進的設備歷史資料，檢測此段時間中預測結果與實際維修情況是否相符，進而作為門檻值是否調整之依據。Thereafter, the threshold value can be adjusted automatically at regular intervals, and the new equipment history data can also be used to detect whether the predicted result during this period of time is consistent with the actual maintenance situation, and then used as the basis for whether the threshold value is adjusted.
第4圖為本揭露一實施例之門檻值自適化之方法的流程圖。如圖所示，當每隔一段時間後，可針對門檻值作自適化調整，首先，會先取的冷凍冷藏櫃之設備歷史維修資料，並且透過冷凍冷藏櫃之設備歷史資料計算出設備歷史變異數，為了推估設備歷史資料中冷媒狀態，故也會於此設立一個門檻值，此稱為初始門檻值，接著計算該設備歷史變異數與該初始門檻值之比值，以於比值大於1時判斷冷媒洩漏，以及於該比值不大於1時判斷冷媒未洩漏，其中上述結果都稱為預測結果。Figure 4 is a flow chart of a method for threshold self-adjustment in an embodiment of the disclosure. As shown in the figure, after a certain period of time, the threshold value can be adjusted automatically. First, the equipment historical maintenance data of the freezer and refrigerator will be taken first, and the historical variance of the equipment will be calculated through the equipment history data of the freezer and refrigerator. In order to estimate the state of the refrigerant in the historical data of the equipment, a threshold is also set here, which is called the initial threshold, and then the ratio of the historical variance of the equipment to the initial threshold is calculated to determine when the ratio is greater than 1. The refrigerant leaks, and when the ratio is not greater than 1, it is judged that the refrigerant does not leak, and the above results are all called prediction results.
後續，比對設備歷史維修資料與預測結果是否相符，若是則表示預測正確，反之則為預測錯誤，接著可根據預測正確和預測錯誤比例來計算準確度，並於準確度低於一預設標準時，進行門檻值的調整。另外，門檻值自適化之方法同樣也可於第2圖所述的雲端伺服器中執行，除了可利用雲端資料庫內龐大設備歷史資料外，也可設定定時檢測門檻值是否適合，當有須要調整門檻值時，自適化後的門檻值可被傳送至該冷凍冷藏櫃的紀錄器。Afterwards, compare the historical maintenance data of the equipment with the predicted result. If it is, the prediction is correct, otherwise, the prediction is wrong. Then, the accuracy can be calculated based on the ratio of correct prediction to prediction error, and when the accuracy is lower than a preset standard , Adjust the threshold value. In addition, the threshold value self-adjustment method can also be executed in the cloud server described in Figure 2. In addition to using the huge device history data in the cloud database, you can also set the timing to check whether the threshold value is suitable, when necessary When adjusting the threshold value, the adjusted threshold value can be transmitted to the recorder of the refrigerating cabinet.
第5圖為本揭露一實施例之非侵入式冷媒洩漏偵測系統的示意圖。本揭露之非侵入式冷媒洩漏偵測系統可應用於冷凍冷藏櫃的冷媒洩漏偵測，該系統可架設於雲端伺服器中，由該雲端伺服器之處理器所執行之程式進行運算與分析，另外資料可儲存於雲端伺服器的雲端資料庫內，因而冷凍冷藏櫃與雲端伺服器和雲端資料庫間可傳遞資料，惟非侵入式冷媒洩漏偵測系統不以雲端架設為限，亦可架設於冷凍冷藏櫃內或是由周邊電子設備來運行。如圖所示，本揭露之非侵入式冷媒洩漏偵測系統1包括資料收集模組11、計算模組12、門檻值模組13以及判斷模組14。FIG. 5 is a schematic diagram of a non-invasive refrigerant leakage detection system according to an embodiment of the disclosure. The non-intrusive refrigerant leakage detection system disclosed in the present disclosure can be applied to refrigerant leakage detection in refrigerated cabinets. The system can be installed in a cloud server, and the program executed by the cloud server's processor performs calculation and analysis. In addition, data can be stored in the cloud database of the cloud server, so data can be transferred between the freezer and the cloud server and the cloud database. However, the non-intrusive refrigerant leakage detection system is not limited to the cloud architecture and can also be set up Operate in the freezer and refrigerator or by peripheral electronic equipment. As shown in the figure, the non-invasive refrigerant
資料收集模組11用於取得冷凍冷藏櫃之運作模式輸出值7以及位於該冷凍冷藏櫃內之溫度感測器所感測之溫度值8。簡言之，資料收集模組11可接收冷凍冷藏櫃端所傳送的資料，例如冷凍冷藏櫃可設有資料收集接受器來收集該冷凍冷藏櫃之運作模式輸出值7以及位於該冷凍冷藏櫃內之溫度感測器所感測之溫度值8，接著傳送給資料收集模組11以進行資料收集。The
計算模組12用於利用該運作模式輸出值7取得該冷凍冷藏櫃之除霜間隔時間，以一個除霜間隔時間作為一時窗，藉此計算每一時窗內該溫度值8之平均溫度值以及該每一時窗內該平均溫度值的變異數。為了判斷冷媒洩漏與否，須將資料進行解析，包括取得平均值和變異數並與門檻值進行比對，具體來說，依據該冷凍冷藏櫃之運作模式輸出值7可得到該冷凍冷藏櫃之除霜間隔時間，也就是依據除霜間隔時間切割為一個時窗，故依據整個運作模式下，可被切割出多個時窗，接著，計算每一時窗內溫度值8之平均溫度值，並且以該每一時窗內該平均溫度值再計算出變異數。The
門檻值模組13用於透過設備歷史資料9取得建議門檻值。門檻值模組13用於取得建議門檻值，須說明者，該建議門檻值為一個自適化門檻值，有關自適化後面會再說明。The
判斷模組14用於計算該平均溫度值的變異數與該建議門檻值之比值，以於該比值大於1時，判斷為冷媒洩漏之狀況。簡言之，該判斷模組14係將該平均溫度值的變異數除以該建議門檻值，兩者所得到比值作為冷媒洩漏判斷依據，當比值大於1時表示冷媒洩漏，當該比值不大於1時，則表示冷媒沒有洩漏。The judging
綜上可知，本揭露使用冷凍冷藏櫃其溫控器現有的溫度感測器(例如出風口溫度感測器或蒸發器溫度感測器)，利用出風口溫度與運轉模式，收集冷凍冷藏櫃的設備歷史資料9，藉此計算出變異數、平均值和門檻值，進而判斷故障狀態。In summary, the present disclosure uses the existing temperature sensor (such as the air outlet temperature sensor or the evaporator temperature sensor) of the temperature controller of the freezer-refrigerator, and uses the air outlet temperature and operation mode to collect the temperature of the freezer-refrigerator
第6圖為本揭露另一實施例之非侵入式冷媒洩漏偵測系統的示意圖。如前所述，門檻值模組13能依據一段時間的結果來決定門檻值，亦即該門檻值模組13於每隔一預設時間依據歷史紀錄比較結果自適化調整該建議門檻值，因而本實施例所述系統與第5圖相似，兩者差異僅在於門檻值模組13包括儲存單元131、運算單元132以及自適化單元133。FIG. 6 is a schematic diagram of a non-invasive refrigerant leakage detection system according to another embodiment of the disclosure. As mentioned above, the
具體來說，該儲存單元131用於儲存冷凍冷藏櫃之歷史維修紀錄以及設備歷史資料，該運算單元132用於依據該設備歷史資料計算出該冷凍冷藏櫃之設備歷史變異數，並且計算該設備歷史變異數與預設之初始門檻值之歷史比值，俾依據該歷史比值判斷冷媒狀態以得到預測結果。也就是說，同樣透過設備歷史資料進行時窗切割，計算每一個時窗的溫度平均值和歷史變異數，接著計算歷史變異數與預設之初始門檻值之比值，同樣地，比值大於1表示冷媒洩漏，反之則設備正常，最終得到預測結果。Specifically, the
自適化單元133用於比對該預測結果與該歷史維修紀錄，藉以判定該初始門檻值之準確性，俾依據該準確性調整該初始門檻值而作為該建議門檻值。自適化單元133係將預測結果與真實的設備歷史維修紀錄進行比對，藉以判斷門檻值(初始門檻值)之準確性，並於需要時調整該初始門檻值，而調整後的門檻值，即作為現行判斷冷媒洩漏之用的建議門檻值。The
本揭露的模組、裝置、設備、伺服器等包括微處理器及記憶體，而演算法、資料、程式等係儲存記憶體或晶片內，微處理器可從記憶體載入資料或演算法或程式進行資料分析或計算等處理，在此不予贅述。例如本揭露之非侵入式冷媒洩漏偵測系統內各模組包括有微處理器與記憶體等，故能執行分析運算，因而本揭露所述之模組、單元或設備等其硬體細部結構亦可以相同實現方式。The modules, devices, equipment, servers, etc. disclosed in this disclosure include microprocessors and memory. Algorithms, data, programs, etc. are stored in memory or chips. The microprocessor can load data or algorithms from memory. Or procedures for data analysis or calculation, etc., will not be repeated here. For example, each module in the non-intrusive refrigerant leakage detection system of the present disclosure includes a microprocessor and a memory, etc., so it can perform analysis calculations. Therefore, the hardware details of the modules, units, or equipment described in this disclosure are structured It can also be implemented in the same way.
第7A和7B圖為本揭露一具體實施例中溫度平均值與變異數計算的示意圖。如前所述，要執行溫度平均值與變異數之計算時，會以除霜間隔時間作為時窗(n)，首先，利用計算式
因此，如第7A圖所示，以除霜間隔時間作為時窗(n)，故可分為時窗T
1-T
5，若變異數(T
var)與門檻值(V
th)之比值(
以第7A圖為基礎，圖中標示了一日時間(24小時)內每一個小時的出風溫度，即每日各設備記錄除霜時間和非除霜時間之出風溫度值，當要計算平均溫度值時，排除除霜時間的部分後會切割為T
1~T
5共五個時窗，接著，計算各時窗內的平均溫度(
T
i )，其中，
接著，計算各時窗內平均溫度之平均值，即
最後，利用下面方程式計算變異數與建議門檻值之比值是否大於1，其中建議門檻值預設為0.5，該方程式為：變異數/門檻值= 7.6/0.5 = 15.2，此時比值大於1，判定為冷媒洩漏。Finally, use the following equation to calculate whether the ratio of the variance to the recommended threshold is greater than 1, where the recommended threshold is preset to 0.5. The equation is: variance/threshold = 7.6/0.5 = 15.2. At this time, the ratio is greater than 1. It is a refrigerant leak.
前述說明可比對冷凍冷藏櫃過去設備歷史資料所算出的比值與實際維修紀錄，確認門檻值設定與偵測準確率的關係。經實驗可知，當冷凍冷藏櫃預測故障準確率於V th=0.5 時，準確度達最高，如第8圖所示，因而本揭露建議門檻值可設定為0.5，並於每隔一段時間依據比較結果自適化調整門檻值設定，假設下一次比對結果為V th=0.75時準確度最高，則可將調整門檻值提高為0.75。 The foregoing description can compare the ratio calculated by the past equipment history data of the refrigerating cabinet with the actual maintenance record, and confirm the relationship between the threshold setting and the detection accuracy. Experiments show that when the prediction accuracy of the refrigerating cabinet is at V th = 0.5, the accuracy is the highest, as shown in Figure 8. Therefore, the recommended threshold of this disclosure can be set to 0.5, and compare it at regular intervals. The result is an adaptive adjustment threshold setting. Assuming that the accuracy of the next comparison is V th =0.75, the adjustment threshold can be increased to 0.75.
綜上所述，本揭露提出的非侵入式冷媒洩漏偵測系統、其方法以及其門檻值自適化之方法，係利用出風口或蒸發器之溫度感測器所感測溫度以及冷凍冷藏櫃之運轉模式，收集冷凍冷藏櫃之設備歷史資料，透過自主學習方式計算出變異數、平均值和門檻值，並利用變異數和自適化門檻值關係判斷故障狀態，如此在無須增加額外成本下，能以現有設備及冷媒洩漏偵測演算法推測出冷媒洩漏狀態並能即時告警以進行維修。In summary, the non-intrusive refrigerant leakage detection system, its method, and the threshold value self-adjustment method proposed in this disclosure utilize the temperature sensed by the temperature sensor of the air outlet or the evaporator and the operation of the refrigerating cabinet Mode, collect the equipment history data of the refrigerating cabinet, calculate the variance, average value and threshold value through self-learning method, and use the relationship between the variance and the adaptive threshold value to judge the fault state, so that it can be used without additional cost. Existing equipment and refrigerant leakage detection algorithms infer the state of refrigerant leakage and can immediately alert for maintenance.
雖然本揭露已以實施例揭露如上，然其並非用以限定本揭露，任何所屬技術領域中具有通常知識者，在不脫離本揭露的精神和範圍內，當可作些許的更動與潤飾，故本揭露的保護範圍當視後附的申請專利範圍所界定者為準。Although the present disclosure has been disclosed in the above embodiments, it is not intended to limit the present disclosure. Anyone with ordinary knowledge in the relevant technical field can make some changes and modifications without departing from the spirit and scope of this disclosure. Therefore, The scope of protection of this disclosure shall be subject to the scope of the attached patent application.
1:非侵入式冷媒洩漏偵測系統 11:資料收集模組 12:計算模組 13:門檻值模組 131:儲存單元 132:運算單元 133:自適化單元 14:判斷模組 7:運作模式輸出值 8:溫度值 9:設備歷史資料 S11~S15:步驟 S31~S35:步驟 1: Non-invasive refrigerant leakage detection system 11: Data collection module 12: Calculation module 13: Threshold value module 131: storage unit 132: arithmetic unit 133: Self-adjusting unit 14: Judgment module 7: Operation mode output value 8: Temperature value 9: Equipment history data S11~S15: steps S31~S35: steps
第1圖為本揭露之非侵入式冷媒洩漏偵測方法的步驟圖。 第2圖為本揭露一實施例之非侵入式冷媒洩漏偵測方法的流程圖。 第3圖為本揭露之門檻值自適化之方法的步驟圖。 第4圖為本揭露一實施例之門檻值自適化之方法的流程圖。 第5圖為本揭露一實施例之非侵入式冷媒洩漏偵測系統的示意圖。 第6圖為本揭露另一實施例之非侵入式冷媒洩漏偵測系統的示意圖。 第7A和7B圖為本揭露一具體實施例中溫度平均值與變異數計算的示意圖。 第8圖為本揭露一具體實施例中門檻值與故障預測準確度的比較圖。 Figure 1 is a step diagram of the disclosed non-invasive refrigerant leakage detection method. FIG. 2 is a flowchart of a non-invasive refrigerant leakage detection method according to an embodiment of the disclosure. Figure 3 is a step diagram of the threshold self-adjustment method disclosed in this disclosure. Figure 4 is a flow chart of a method for threshold self-adjustment in an embodiment of the disclosure. FIG. 5 is a schematic diagram of a non-invasive refrigerant leakage detection system according to an embodiment of the disclosure. FIG. 6 is a schematic diagram of a non-invasive refrigerant leakage detection system according to another embodiment of the disclosure. Figures 7A and 7B are schematic diagrams illustrating the calculation of the average temperature and the variance in a specific embodiment of the disclosure. Fig. 8 is a comparison diagram of the threshold value and the accuracy of fault prediction in a specific embodiment of the disclosure.
S11~S15:步驟 S11~S15: steps
Claims (10)
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW108138517A TWI722617B (en) | 2019-10-25 | 2019-10-25 | System and method for a non-intrusive refrigerant leakage detection and adaptive method for threshold thereof |
| CN201911192347.XA CN112710120B (en) | 2019-10-25 | 2019-11-28 | Non-invasive refrigerant leakage detection system, method and threshold value self-adaption method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW108138517A TWI722617B (en) | 2019-10-25 | 2019-10-25 | System and method for a non-intrusive refrigerant leakage detection and adaptive method for threshold thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| TWI722617B true TWI722617B (en) | 2021-03-21 |
| TW202117240A TW202117240A (en) | 2021-05-01 |
Family
ID=75541123
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| TW108138517A TWI722617B (en) | 2019-10-25 | 2019-10-25 | System and method for a non-intrusive refrigerant leakage detection and adaptive method for threshold thereof |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN112710120B (en) |
| TW (1) | TWI722617B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW201411058A (en) * | 2012-09-14 | 2014-03-16 | China Steel Corp | Monitoring system of air conditioning unit |
| CN109186041A (en) * | 2018-12-05 | 2019-01-11 | 新誉轨道交通科技有限公司 | A kind of undesirable judgment method of air conditioner refrigerating and device |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6260365B1 (en) * | 2000-01-07 | 2001-07-17 | Traulsen & Company, Inc. | Control system and related methods for refrigeration and freezer units |
| KR20050028391A (en) * | 2003-09-17 | 2005-03-23 | 엘지전자 주식회사 | A refrigerants leakage sensing system and method |
| DE102006016558A1 (en) * | 2006-04-07 | 2007-10-11 | Air Liquide Deutschland Gmbh | Method for monitoring the gas-tightness of a cooling system of a refrigerated vehicle and for operating the same and cooling system for a refrigerated vehicle and refrigerated vehicle |
| JP6304330B2 (en) * | 2016-09-02 | 2018-04-04 | ダイキン工業株式会社 | Refrigeration equipment |
-
2019
- 2019-10-25 TW TW108138517A patent/TWI722617B/en active
- 2019-11-28 CN CN201911192347.XA patent/CN112710120B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW201411058A (en) * | 2012-09-14 | 2014-03-16 | China Steel Corp | Monitoring system of air conditioning unit |
| CN109186041A (en) * | 2018-12-05 | 2019-01-11 | 新誉轨道交通科技有限公司 | A kind of undesirable judgment method of air conditioner refrigerating and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112710120A (en) | 2021-04-27 |
| CN112710120B (en) | 2022-08-16 |
| TW202117240A (en) | 2021-05-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| AU2022201272B2 (en) | Maintenance and diagnostics for refrigeration systems | |
| JP3418009B2 (en) | Method and apparatus for monitoring and managing refrigeration equipment | |
| US7921660B2 (en) | System and method for controlling defrost cycles of a refrigeration device | |
| US20160299038A1 (en) | System and method for remotely inferring characteristics of thermostat-controlled appliances | |
| JP5362692B2 (en) | Cooling performance deterioration diagnosis system for refrigerator and cooling performance deterioration diagnosis method for refrigerator | |
| JP4572447B2 (en) | Failure diagnosis method, failure diagnosis device, and recording medium | |
| TWI722617B (en) | System and method for a non-intrusive refrigerant leakage detection and adaptive method for threshold thereof | |
| JP2004113681A (en) | Maintenance time determination method, fault diagnostic device and program | |
| JP2011174685A (en) | Gas leakage detection method | |
| JP3604905B2 (en) | Failure judgment system | |
| EP4227603A1 (en) | A method for generating early temperature warning in a vapour compression system | |
| US6342840B1 (en) | Service controller for temperature-controlled appliances | |
| JPH0682131A (en) | Method and apparatus for monitoring and controlling refrigerating equipment | |
| JP6583779B2 (en) | Refrigeration system | |
| JP2008249226A (en) | Refrigerant leakage detecting method of refrigerating device | |
| JP6587131B2 (en) | Refrigeration system | |
| JPH0493567A (en) | Device for diagnosing performance of freezer | |
| JP2023089435A (en) | Information processing device, program, abnormality detection method, abnormality detection system, and cooling storage shed | |
| KR102051021B1 (en) | Apparatus for predicting and detecting malfunction of deep freezer | |
| KR102583019B1 (en) | Artificial Intelligence Refrigerator with failure prediction function | |
| CN110411086B (en) | Filter blockage judging method, multi-connection air conditioner and readable medium | |
| US20240102677A1 (en) | Systems and methods for predicting refrigerant leakage of a critically charged hvac/refrigeration system | |
| JP2017161207A (en) | Refrigeration system | |
| JP2006183941A (en) | Liquid return prediction system, method for predicting liquid return in refrigerator, and program for predicting liquid return |