•4 1364519 t 六、發明說明： 【發明所屬之技術領域】 • 本發明係關於一種性能檢測方法，詳而言之，係為一 種高準確度的空調設備之性能特性檢測方法。 【先前技術】 近年來，隨著經濟的起飛與產業的快速發展，用電量 • 與用電需求也隨著大幅增加。但是由於發電容易產生環境 • 污染（例如：二氧化碳的排放所造成氣候暖化）、電廠的土 ^ 地取得不易，且電力來源的開發速度與輸配電系統的建設 腳步並無法滿足日益增加的用電量與用電需求，以致供電 量常常發生不足，而導致了於尖峰用電時段需要限制用電 量的措施。因此，如何有效地節約電能來避免供電量不足， 遂成為社會各界努力的目標。 根據統計，各種用電設備中通常又以空調設備所佔的 用電比例最大，舉例而言，實際的半導體廠房中的用電設 φ 備有製程設備、測試設備及/或空調設備，而空調設備（例 如：恆溫水槽、空調系統、冰水主機等）通常佔了該半導 體廠房用電總量的百分之二十七以上，因此可以合理推 知，從提高空調設備的使用效率為主要目標來著手，即為 一種有效的節約電能之方法。 而若欲提高空調設備的使用效率，除了依據不同的使 用環境來選擇性能最適合的空調設備之外，也必須準確、 即時地得知該空調設備的性能特性，進而得以依據該空調 設備的性能特性調整該空調設備之使用方式。或者是提前 111303 1364519 維修性能狀況出問題的空調設備，以避免電能無形中的耗-損或者是空調設備臨時發生故障。然而，現有的空調設備 之性能檢測方法，大多是依據空調設備供應商於出廠時所 測試的運轉參數（例如：冷凍能力等），配合空調設備之維 護人貝的經驗來予以分析及檢測以得知該空調設備的性能 特性。 惟，現今實際的空調設備大多使用於多變量的使用環 境中，且大多的空調設備（例如冰水主機）於出廠前所作 之檢測資訊，僅於特定的測試環境具有參考價值。再者， 空調設備之運轉特性，亦會隨著設計架構、運轉時間以及 保養狀況等因素而有所改變，例如會隨著運轉時數、維護 保養品質、冰水主機的效率、周邊設備的變化或工作班次 而跟著改變。當然，空調設備的系統運作情形亦會隨著環 境之外氣因素，例如氣候、溫度、濕度、季節性循環等因 素而有所變化。 因此，若利用現有的檢測方式來檢測空調設備的性能 特性（例如人為、歷史經驗法則），不但準確度不高，也無 法即時、有效地掌握空調設備的運作情形，且無法彈性地 調整空調設備的使用方式，亦無法提供相關的維修或保養 人員彈性地調整空調設備的保養排程。 是故，如何提供一種應用於空調設備之性能檢測方 法，能即時'準確、有效地掌握空調設備的性能特性，以 彈性地調整空調設備的使用方式及/或保養排程、降低空調 設備發生臨時故障的機率，進而避免成本的損耗與電能的 4 1Π303 1364519 赛費，遂成為各界亟待解決之課題。 【發明内容】 • 為解決上述各界亟待解決之課題，本發明提供一種性 能檢測方法，係對空調設備在實際運轉狀態下所擷取到之 實際運轉參數進行檢測、分析，進而得知該空調設備之性 能特性，該性能檢測方法包括以下步驟··（ 1)於該空調設 備在標準運轉狀態時，擷取該空調設備之標準運轉參數； (2)依據該空調設備之標準運轉參數，產生該空調設備於 ® 標準運轉狀態下的性能模型；（3 )依據該性能模型對擷取 到之該實際運轉參數進行分析，並判斷出該空調設備的性 能特性；以及（4)若判斷出該空調設備的性能特性發生異 常時，予以警示，而若判斷出該空調設備的性能特性係為 正常時，擷取該空調設備在實際運轉狀態下之實際性能並 返回該步驟（3 )，進而持續地進行檢測。 於本發明之一較佳實施態樣，該空調設備係為冷氣 φ 機、中央空調系統及/或冰水主機。而該標準運轉參數與該 實際運轉參數，係分別為該空調設備於標準運轉狀態與實 際運轉狀態的耗電比例（Power Rate)、耗電量、能源效率 比值（Energy Efficiency Rate)、性能係數（Coefficient of Performance)、冷凌負荷（Part Load Ratio ; PLR)、每冷;東 。頓所消耗的電功率、冷卻水出回水溫度、冷卻水流量、冰 水出回水溫度、冰水流量、冷媒壓力及/或外氣溫濕度等。 於本發明之另一較佳實施態樣，該性能模型係可以趨 勢圖及/或曲線圖之形式來予以呈現。此外，係可利用落點 ]11303 1364519 分析、_分巍/·聯性純 到之該空調設備之實際運轉參數進行分析。 因此，相較於習知技術，本發明之性能檢測方法，不 但“ 了檢測的準確度，可即時、有效地掌握空綱 性=性與運作情形，提供相關的維修或保養人員料地 用方式及/或保養排程，進而減低空調設 形，並避免電能的浪費與成本的損耗。 式，由特定的具體實施例說明本發明之實施方 式熟悉此技術之人士可由本說明書所揭示之内容 瞭解2明之其他優點與功效。本發明亦可藉由其他二不同 的具體貫施例加以施行或應用。 ·- -般常見的空調設備，其主要可分為產出物質率统盘 冷部物質系統’而該空調設備係藉由產出 卻 物質系統之間的熱交換作用，不斷產出適合的產出物Γ Γ冰水、冷氣等。舉例而言，冷氣機、中央空調系統與 冰水主機，皆為一般常見的空調設備。 ·… 請參考第！圖，其係清楚示意出冰水主機】，且 水主機1係包含產出物質系統與冷卻物質系統U。 如圖所示，該冰水主撼_ 1么 Λ人王機1係稭由產出物質系統 Γ物質系統11之間的熱交換作用，將高溫冰水降溫以輸 s ^即可利用該低溫冰水提供後續相關的 衣心或廠似施予以利用（利㈣低溫冰水予以降溫 然’亦可使用相關的量測設備量測出該冰水主機]之心 1Π303 6 1364519 溫度、外氣相對濕度、冷媒水質、高溫冰水溫度、冷媒入 水溫度、冷媒出水溫度以及低溫冰水溫度等運轉參數。 請參閱第2圖，其係繪示本發明之性能檢測方法之步 驟流程示意圖，且該性能檢測方法係可應用於空調設備上。• 4 1364519 t VI. Description of the invention: [Technical field to which the invention pertains] The present invention relates to a performance detecting method, and more specifically, to a method for detecting performance characteristics of a high-accuracy air-conditioning apparatus. [Prior Art] In recent years, with the take-off of the economy and the rapid development of the industry, the demand for electricity consumption and electricity consumption has also increased significantly. However, due to the fact that power generation is prone to environmental pollution (eg, climate warming caused by carbon dioxide emissions), the power generation of power plants is not easy, and the development speed of power sources and the construction of transmission and distribution systems cannot meet the increasing power consumption. The amount of electricity used and the demand for electricity often cause insufficient power supply, which leads to measures that need to limit the amount of electricity used during peak hours. Therefore, how to effectively save energy to avoid insufficient power supply has become a goal of all walks of life. According to statistics, the proportion of electricity used by air-conditioning equipment is usually the largest among various electrical equipment. For example, the actual power supply in the semiconductor factory is equipped with process equipment, test equipment and/or air-conditioning equipment, and air-conditioning equipment. (for example, constant temperature water tanks, air conditioning systems, ice water mains, etc.) usually account for more than 27% of the total electricity consumption of the semiconductor plant, so it can be reasonably inferred that the main goal is to improve the efficiency of air conditioning equipment. Is an effective way to save energy. In order to improve the efficiency of air-conditioning equipment, in addition to selecting the most suitable air-conditioning equipment according to different use environments, the performance characteristics of the air-conditioning equipment must be accurately and immediately known, and then the performance of the air-conditioning equipment can be obtained. The characteristics adjust the way the air conditioner is used. Or in advance 111303 1364519 maintenance air conditioning equipment with performance problems, to avoid the invisible loss of power or the temporary failure of air conditioning equipment. However, the existing methods for detecting the performance of air-conditioning equipment are mostly based on the operating parameters (for example, refrigeration capacity) tested by the air-conditioning equipment supplier at the factory, and are analyzed and tested with the experience of the maintenance personnel of the air-conditioning equipment. Know the performance characteristics of the air conditioning equipment. However, most of today's actual air-conditioning equipment is used in a multi-variable environment, and most of the air-conditioning equipment (such as ice water mainframes) have test information before leaving the factory, which is only valuable for a specific test environment. In addition, the operating characteristics of air-conditioning equipment will also change with the design structure, operation time and maintenance conditions, such as the number of operating hours, maintenance quality, efficiency of the ice water main unit, and changes in peripheral equipment. Or work shifts and follow changes. Of course, the system operation of air-conditioning equipment will also vary with environmental factors such as climate, temperature, humidity, and seasonal circulation. Therefore, if the existing detection method is used to detect the performance characteristics of the air-conditioning equipment (for example, human-made, historical rule of thumb), not only the accuracy is not high, but also the operation of the air-conditioning equipment cannot be grasped instantaneously and effectively, and the air-conditioning equipment cannot be flexibly adjusted. The way of use does not provide the relevant maintenance or maintenance personnel to flexibly adjust the maintenance schedule of the air conditioning equipment. Therefore, how to provide a performance detection method for air-conditioning equipment can instantly and accurately grasp the performance characteristics of air-conditioning equipment, flexibly adjust the usage mode of air-conditioning equipment and/or maintenance schedule, and reduce the occurrence of air-conditioning equipment. The probability of failure, and thus the cost loss and the 4 1 Π 303 1364519 racing fee of electric energy, has become an urgent issue to be solved. SUMMARY OF THE INVENTION In order to solve the above problems to be solved, the present invention provides a performance detecting method for detecting and analyzing actual operating parameters captured by an air conditioning device in an actual operating state, and further knowing the air conditioning device. The performance characteristic, the performance detecting method comprises the following steps: (1) taking the standard operating parameter of the air conditioning device when the air conditioning device is in a standard operating state; (2) generating the standard operating parameter according to the air conditioning device Performance model of the air conditioning equipment under standard operating conditions; (3) analyzing the actual operating parameters obtained from the performance model and determining the performance characteristics of the air conditioning equipment; and (4) determining the air conditioning When the performance characteristics of the equipment are abnormal, the warning is given. If it is judged that the performance characteristics of the air conditioner are normal, the actual performance of the air conditioner under actual operating conditions is taken and the step (3) is returned, and then continuously Test. In a preferred embodiment of the present invention, the air conditioning device is a cold air φ machine, a central air conditioning system, and/or an ice water host. The standard operating parameter and the actual operating parameter are respectively a power rate, a power consumption ratio, an energy efficiency ratio, and a performance coefficient of the air conditioning device in a standard operating state and an actual operating state. Coefficient of Performance), Part Load Ratio (PLR), every cold; East. Electricity consumption, cooling water return water temperature, cooling water flow rate, ice water return water temperature, ice water flow rate, refrigerant pressure and/or external temperature and humidity. In another preferred embodiment of the invention, the performance model can be presented in the form of a trend graph and/or a graph. In addition, the analysis can be carried out by using the 11303 1364519 analysis and the actual operating parameters of the air conditioner. Therefore, compared with the prior art, the performance detecting method of the present invention not only "accurate the detection degree, but also can instantly and effectively grasp the void pattern = sex and operation situation, and provide related maintenance or maintenance personnel materials. And/or maintenance of the schedule, thereby reducing the air conditioning configuration, and avoiding waste of electrical energy and loss of cost. Embodiments of the present invention will be described by a specific embodiment. Those skilled in the art can understand the contents disclosed in the present specification. 2 other advantages and effects of the invention. The invention can also be implemented or applied by other two different specific embodiments. - - The common air conditioning equipment, which can be mainly divided into the output material rate system 'The air conditioning equipment continuously produces suitable output materials, such as ice water, cold air, etc., through the heat exchange between the output and the material systems. For example, air conditioners, central air conditioning systems and ice water hosts All are common air conditioning equipment. ·... Please refer to the figure!, which clearly shows the ice water main unit, and the water main unit 1 contains the produced material system and cooling material. As shown in the figure, the ice water main 撼 1 Λ Λ 王 wang machine 1 series straw is exchanged by the heat exchange between the material system and the material system 11, and the high temperature ice water is cooled to lose s ^ Use the low-temperature ice water to provide subsequent related clothing or factory-like application (Lie (four) low-temperature ice water to cool down' can also use the relevant measuring equipment to measure the ice water host] heart 1Π303 6 1364519 temperature, Operating parameters such as external air relative humidity, refrigerant water quality, high temperature ice water temperature, refrigerant water inlet temperature, refrigerant outlet water temperature, and low temperature ice water temperature, etc. Please refer to FIG. 2, which is a schematic flow chart showing the steps of the performance detecting method of the present invention. And the performance detection method can be applied to an air conditioner.
於步驟S21中，於該空調設備標準的、日常的運轉狀 態時，擷取複數個空調設備之標準運轉參數，並可予以儲 存。該空調設備係可為冷氣機、中央空調系統及/或冰水主 機（如第1圖所示）。而該標準運轉參數係可為該空調設備 於標準的運轉狀態下之耗電比例（Power Rate )、平均耗電 量、能源效率比值（Energy Efficiency Rate)、性能係數 (Coefficient of Performance )、冷床負荷（Part Load Ratio)、每冷凍°頓所消耗的電功率、冷卻水出回水溫度、 冷卻水流量、冰水出回水溫度、冰水流量、冷媒壓力及/ 或外氣溫濕度等。於本發明之一較佳實施態樣，該步驟S21 係可長時間地以定期、持續之方式，並透過相關的參數擷 取裝置（未圖示）來擷取該空調設備的標準運轉參數，並 可將該標準運轉參數予以儲存。此外，於步驟S21中亦可 設定說明訊息之步驟，該說明訊息包括異常情形、造成該 異常情形的原因，以及該異常情形之處理措施及/或相關的 保養說明，並可予以儲存（例如：可以表格之形式儲存於 相關的資料庫中）。接著進至步驟S22。 於步驟S22中，依據複數個該空調設備之標準運轉參 數，產生該空調設備於正常運轉狀態下的性能模型（如以 下第3圖及第4圖所示）。詳而言之，係可利用所操取到之 7 111303 1364519 複數個該空調設備之標準運轉參數其中至少兩個，加以整-理與歸納以形成一該空調設備於正常運轉狀態下的性能模 型（例如數學模型與趨勢函式）。較佳地，該性能模型係可 以趨勢圖或曲線圖之形式來予以呈現，且可將該性能模型 予以儲存。接著進至步驟S23。 於步驟S23中，係於該空調設備實際的運轉狀態下， 擷取複數個該空調設備的實際運轉參數。該實際運轉參數 係可為該空調設備於實際的運轉狀態下之耗電比例、平均 耗電量、能源效率比值、性能係數、冷凍負荷、每冷凍噸 所消耗的電功率、冷卻水出回水溫度、冷卻水流量、冰水 出回水溫度、冰水流量、冷媒壓力及/或外氣溫濕度等。較 佳地，該步驟S23係可以持續、定期的方式，或者是隨機 啟動的方式，並透過相關的參數擷取裝置來擷取該空調設 備於實際運轉狀態下的實際運轉參數，並可將所擷取到之 該實際運轉參數予以儲存。接著進至步驟S24。 於步驟S24中，依據該性能模型來對所擷取到的實際 運轉參數進行分析，進而可判斷出該空調設備的性能特性 及/或運作情形是否發生異常。因此，若判斷出該空調設備 的性能特性及/或運作情形發生異常狀況時，進至步驟 S25 ;若判斷出該空調設備的性能特性係為正常時，則返 回步驟S23進而持續地進行檢測的步驟。 於本發明之較佳實施態樣，係可以落點分析法來對所 擷取到的實際運轉參數進行分析。而落點分析可包括單一 數值落點分析與數值間關聯落點分析。舉例而言，利用單 8 Π1303 1364519 一數值落點分析可分析出外氣溫度、外氣相對濕度、冰水 入水溫度、冰水出水溫度、冷媒入水溫度以及冷媒出水溫 度等運轉參數是否偏高或偏低，以及偏高或偏低之權重數 值。而利用數值間關聯落點分析可藉由比對過去相似的狀 況下之外氣溫度與冷媒出水溫度，進而得知外氣溫度與冷 媒出水溫度的關聯性是否偏高或偏低，以及偏高或偏低之 權重數值。接著，再利用人工智慧、基因演算法及/或類神 經網路即可判斷出該性能特性發生了異常狀況，進一步亦 可利用人工智慧、基因演算法及/或類神經網路，得知性能 特性發生異常的原因（如下表1、2所列示）。值得一提的 是，於得知性能特性發生異常的原因後，復可將其原因歸 納於相關的知識庫（未圖示）中，以利後續進行設備診斷、 知識庫判斷，進而預防更嚴重的問題發生。 表1(單一數值落點分析） 外氣溫度 外氣相對濕度 冷媒水質 冰水入水溫度 正常(權重0) 正常(權重0) 正常(權重0) 正常(權重0) 冷媒入水溫度 冷媒出水溫度 冰水出水溫度 偏高(權重+1) 偏面(權重+1) 正常(權重0) 表2 (數值間落點分析） 冷媒入水溫度 外氣相對濕度 偏南(權重+】） 正常(權重0) 9 川303 « 亦可::口:i發明之另一較佳實施·態樣，於步驟S24中 來對所擷取到的實際選轉參數進行分析 寺方式 :二或類神經網路等方式來判斷該 W生月匕4寸性及/或運作情形是 n又爾 異常的房因，或者是提,得知且避免;生出發生 ::::得知.___:= = 識庫物Z知術’續續_備診斷及知 於步驟S25中，甚4,,丨^ , 或運作情形發生該^設備祕能特性及/ 簡訊等）。舉例而1 才貝1可提出警示（例如：警報、 作情形、狀況設備的性能特性或運 出警示的同時，二出Γ提出警示。較佳地，當提 述所提供之相關的星能的異常原因，且依據該前 的故障處理料及_目_;;成/^=、因’以及預定 策。詳而言之，可以的處理對 地師選出最有可能的異常㈣ 二二^法，自動 議較佳的故障處理措施及養的原因’進而建 員或保養人員進行檢測、維=養步ν ’以利相關的維修人 ‘ >或保養。如下表3所列示。 1Π303 10 i3645l9In step S21, the standard operating parameters of the plurality of air conditioners are retrieved and stored in the normal operating state of the air conditioner. The air conditioning unit may be an air conditioner, a central air conditioning system, and/or an ice water host (as shown in Fig. 1). The standard operating parameter is the power rate, the average power consumption, the energy efficiency ratio, the coefficient of performance, and the cooling bed of the air conditioner under standard operating conditions. Part Load Ratio, electric power consumed per ton of cooling, cooling water return water temperature, cooling water flow rate, ice water return water temperature, ice water flow rate, refrigerant pressure and/or external temperature and humidity. In a preferred embodiment of the present invention, the step S21 can capture the standard operating parameters of the air conditioning device in a regular, continuous manner and through a related parameter extraction device (not shown) for a long time. The standard operating parameters can be stored. In addition, a step of specifying a message may be set in step S21, the description message including an abnormal situation, a cause of the abnormal situation, and a treatment measure of the abnormal situation and/or related maintenance instructions, and may be stored (for example: It can be stored in the relevant database in the form of a table). Then it proceeds to step S22. In step S22, a performance model of the air conditioner in a normal operating state is generated according to a plurality of standard operating parameters of the air conditioner (as shown in Figures 3 and 4 below). In detail, at least two of the standard operating parameters of the air conditioner can be used to form a performance model of the air conditioner under normal operating conditions. 7 111303 1364519 (eg mathematical models and trend functions). Preferably, the performance model can be presented in the form of a trend graph or a graph and the performance model can be stored. Then it proceeds to step S23. In step S23, a plurality of actual operating parameters of the air conditioning device are retrieved in the actual operating state of the air conditioning device. The actual operating parameter may be the power consumption ratio, the average power consumption, the energy efficiency ratio, the coefficient of performance, the refrigeration load, the electric power consumed per ton of refrigeration, and the temperature of the return water of the cooling water in the actual operating state of the air conditioner. , cooling water flow, ice water return water temperature, ice water flow, refrigerant pressure and / or outside temperature and humidity. Preferably, the step S23 can be performed in a continuous, regular manner, or in a random manner, and the actual parameter of the air conditioner in the actual operating state can be retrieved through the relevant parameter extraction device, and the The actual operating parameters retrieved are stored. Then it proceeds to step S24. In step S24, the captured actual operating parameters are analyzed according to the performance model, and then it is determined whether the performance characteristics and/or operating conditions of the air conditioning device are abnormal. Therefore, if it is determined that the performance characteristics and/or the operation condition of the air conditioner is abnormal, the process proceeds to step S25. If it is determined that the performance characteristic of the air conditioner is normal, the process returns to step S23 to continuously perform the detection. step. In a preferred embodiment of the invention, the actual operating parameters retrieved can be analyzed by a drop point analysis method. The drop analysis can include a single numerical drop analysis and an inter-value drop analysis. For example, using a single 8 Π 1303 1364519 numerical drop analysis can analyze whether the operating parameters such as outside air temperature, external air relative humidity, ice water inlet temperature, ice water outlet temperature, refrigerant inlet water temperature, and refrigerant outlet temperature are high or partial. Low, and the weight value of the high or low. By using the correlation between the numerical values, the correlation between the outside air temperature and the refrigerant outlet temperature can be determined by comparing the outside air temperature with the refrigerant outlet temperature, and whether the correlation between the outside air temperature and the refrigerant outlet temperature is higher or lower, and higher or Low weight value. Then, artificial intelligence, gene algorithm and/or neural network can be used to judge the abnormality of the performance characteristics, and the artificial intelligence, gene algorithm and/or neural network can be used to learn the performance. The cause of the abnormality of the characteristics (as listed in Tables 1 and 2 below). It is worth mentioning that after knowing the cause of the abnormal performance characteristics, the reason can be summarized in the relevant knowledge base (not shown), in order to facilitate subsequent device diagnosis, knowledge base judgment, and thus prevent more serious The problem has happened. Table 1 (single value drop point analysis) Outside air temperature Outside air relative humidity Refrigerant water quality Ice water into water temperature normal (weight 0) Normal (weight 0) Normal (weight 0) Normal (weight 0) Refrigerant water temperature refrigerant effluent temperature ice water The effluent temperature is high (weight +1) eccentricity (weight +1) normal (weight 0) Table 2 (interval between numerical values) Refrigerant water temperature outside air relative humidity south (weight +)) normal (weight 0) 9 Chuan 303 « can also be:: mouth: another preferred implementation of the invention, in step S24 to analyze the actual selection of the selected parameters of the temple: two or a neural network Judging that the W-monthly 寸 4 inch and / or operating situation is an abnormal cause of n and Er, or mention, learn and avoid; birth occurs:::: learned. ___: = = know the library Z know Surgery 'continued _ preparation diagnosis and knowledge in step S25, even 4, 丨 ^, or the operation situation of the device secret characteristics and / newsletter, etc.). For example, only 1 can raise a warning (for example, an alarm, a situation, a performance characteristic of a conditional device, or a warning to be issued, and a warning is issued. Preferably, when referring to the related star energy provided The cause of the abnormality, and according to the previous fault treatment material and _ _ _;; into / ^ =, because 'and the predetermined policy. In detail, the treatment can be selected for the geographer the most likely abnormal (four) two two ^ method, Automatically discuss the better fault handling measures and reasons for raising 'and then the builder or maintenance personnel to carry out the test, dimension = step ν ' to facilitate the relevant maintenance personnel ' > or maintenance. As shown in Table 3 below. 1Π 303 10 i3645l9
表3 異 常情形 --'~~~·' 造成異常的可能原因 —-----_ 「 -- —- 建議的故障處理措施及/或 保養步驟 遽轉效率 偏低 ^___—--- (水冷式)水管堵塞或水 流太慢。（氣冷式）散 熱片髒汙或散熱風扇 故障。 ------- (水冷式）請清洗過濾器；請 更換修理浮球；請檢查水 位；請清理冷凝器。（氣冷 式）請清潔或更換散熱片。 凃媒温度 過高 大氣濕球過高、風扇故 障或冷卻塔通風不良。 請加大水塔；請檢^ 請淨空水塔空氣出入口。 請檢修冰水機是否 障。 冰水溫度 過高 一____ ----— 冰水機不當運轉。 冷媒溫差 過大 冷媒流量過小。 ~-— 請檢修濾閥是否堵塞 基即建請清洗濾閥；請檢杳 間門是否可正常開啟；請清 洗水垢。 冷媒量不 足 高壓過高或低壓過低。 建議可充填冷媒。 ---—^ 請參閱第3圖係清楚緣示出該空調設備於標準的運轉 狀態下，以相關的參數擷取裝置長時間地、定期、持續: 擷取該空調設備之標準運轉夢數（耗電比例與冷凍負荷） 後’再經過整理與歸納後所產生的性能模型（數學模型 ]] Π1303 1364519 形係可〜== 斷出空調設備的性能特性或運作情 演算法來 表現值）位於該趨勢線之上方=，點（量測 備之性能特性與運轉狀況越來越差。當然，亦== =/或麵等分析方式，來分析該空調設備的實“ 轉麥數與標準運轉參數之間的關係。 不 請參閱第6圖係清楚繪示出利用如第 來對操取到的實際運轉參數進行分析 —二==丄= 亚非位於較佳區域中，因此，即可判斷出p〜、見值） 能特性、運作情形或運轉狀況可能發生了 生 亦可利相歸分析及/或_雜分析等 〃田… :調=?實=轉參數與標準運轉參數之=: 付^的疋，於性能係數（y#〇與冷;東負荷（ 構成的性能曲線巾，曲線的料區 能特性的較佳表現區域。 Μ …周叹備的性 综上所述，本發明之性能檢測方法具有以下優點. 提』=。可透過自動化與規範化的檢S’程序， ⑺預先警示。藉由分析可判斷出 特性或運作情形是否發生異常’或者是是否即將 重的故障。因此，即可彈性地調整不適當的使时式與調艾 Π1303 13 4排軽，進而節省電能的損耗與避免空調設備發生臨 、故障或更嚴4的故障之情形。 (3 )快速處理。可快速協助相關的維修人員 人員恤诽敕、* 只·^ 1示臀 、、、屋4可能故障之原因，進而自動提供至少—種較 乜的建議處理對策。 古據此，不但可解決一般習知技術中檢測結果準確度不 :::問題，亦可即時、準確、有效地掌握空調設備的：能 、運作情形與運轉狀況，並據此彈性地調整空調設備 =使用方式及/或保養触’以及降心糖備發生臨時故 早的機率’進而避免成本的損耗與電能的浪費。 惟，上述實施例僅為例示性說明本發明之原理及其功 效:而非用於限制本發明。奸熟習此項技術之人均^在 ==背本發明之精神及範訂，對上述實施例進行修飾與 【圖式簡單說明】 第1圖係為冰水主機之架構示意圖； 第2圖絲本發明之_檢财法之步驟流程示意 第3圖係為耗電比例與冷;東負荷之性能模型示音圖. 第4圖係為性能係數與冷;東負荷之性能模型示意圖·’Table 3 Abnormal Situations--'~~~·' Possible Causes of Abnormality ----- _ " ---- Suggested troubleshooting measures and / or maintenance steps are not efficient ^___---- (water-cooled) water pipe blocked or water flow is too slow. (air-cooled) heat sink dirty or cooling fan failure ------- (water-cooled) please clean the filter; please replace the repair float; please check the water level Please clean the condenser. (Air-cooled) Please clean or replace the heat sink. The temperature of the coating medium is too high, the atmospheric wet bulb is too high, the fan is faulty or the cooling tower is poorly ventilated. Please increase the water tower; please check the air purifier air inlet and outlet. Please check whether the ice water machine is obstructed. The ice water temperature is too high ____ ----- The ice water machine is not working properly. The refrigerant temperature difference is too large, the refrigerant flow is too small. ~-- Please check whether the filter valve is blocked or not, please clean the filter. Valve; please check if the door can be opened normally; please clean the scale. The refrigerant quantity is not high pressure too high or the low pressure is too low. It is recommended to fill the refrigerant. ----^ Please refer to the figure 3 to clearly show the air conditioner Under standard operating conditions, with relevant parameters Take the device for a long time, on a regular basis, and continue: After taking the standard operating dreams of the air-conditioning equipment (power consumption ratio and refrigeration load), the performance model (mathematical model) produced after finishing and summarizing Π1303 1364519 Can be ~== break out the performance characteristics of the air conditioning equipment or the operational performance algorithm to represent the value) above the trend line =, point (the performance characteristics and operating conditions of the measurement preparation are getting worse and worse. Of course, also == = / or surface analysis method to analyze the relationship between the actual "transfer number" of the air-conditioning equipment and the standard operating parameters. Please refer to Figure 6 to clearly illustrate the actual operating parameters obtained by using the first pair. Perform analysis-two==丄=Asia-Africa is located in the preferred area, so it can be judged that p~, see value) energy characteristics, operation conditions or operating conditions may occur and may be analyzed and/or _ Miscellaneous analysis, etc. 〃田... :调=? Real = conversion parameters and standard operating parameters =: ^ 疋, in the coefficient of performance (y# 〇 and cold; east load (constituting the performance curve towel, the curve of the material area The better performance area of the feature. In summary, the performance detecting method of the present invention has the following advantages: 提 』. Through the automated and standardized inspection S' program, (7) pre-warning. By analysis can determine whether the characteristics or operating conditions are abnormal ' Or whether it is a heavy fault. Therefore, it is possible to flexibly adjust the improper timing and the adjustment of the 1303 13 4 drain, thereby saving the loss of electric energy and avoiding the occurrence of faults, faults or more serious of the air conditioner. (3) Quick processing. It can quickly assist the relevant maintenance personnel to worry about the situation, *only·^ 1 indicates the cause of the hip, and the house 4 may be faulty, and then automatically provide at least a more reasonable advice. According to this, not only can the accuracy of the detection result in the conventional technology be solved:::, the problem can be grasped instantaneously, accurately and effectively: the energy, operation and operation status, and the air conditioner can be flexibly adjusted accordingly. Equipment = use and / or maintenance touch 'and the chance of a temporary and early occurrence of heart-thickness sugar' to avoid cost loss and waste of electrical energy. However, the above-described embodiments are merely illustrative of the principles of the invention and its advantages, and are not intended to limit the invention. The person who is familiar with the technology is modified in the spirit and scope of the invention, and the above embodiment is modified and [simplified description of the drawing] Fig. 1 is a schematic diagram of the structure of the ice water host; The process flow chart of the invention is shown in Fig. 3 as the power consumption ratio and cold; the performance model of the east load is shown in Fig. 4. Fig. 4 is the performance coefficient and the cold;
第5圖係為利用耗電比例與冷;東負荷之性能模型進 落點分析之示意圖；以及 T 第6圖係為利用性能係數與冷清負荷之性能模型 落點分析之示意圖。 】】】3〇3 1364519 【主要元件符號說明】 1 冰水主機 10 產出物質系統 11 冷卻物質系統 S21〜S25 步驟Figure 5 is a schematic diagram of the analysis of the performance model using the power consumption ratio and the cold; east load; and T Fig. 6 is a schematic diagram of the performance model of the performance coefficient and the cooling load. 】]] 3〇3 1364519 [Description of main components] 1 Ice water main unit 10 Material production system 11 Cooling material system S21~S25
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