TWI479311B - System and method for eliminating wrong observed values - Google Patents
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本發明涉及一種監測資料處理系統及方法，尤其關於一種資料處理設備排除其監測資料中的錯誤觀測值的系統及方法。The present invention relates to a monitoring data processing system and method, and more particularly to a system and method for a data processing device to eliminate erroneous observations in its monitoring data.
為了保證資料處理設備（如伺服器）的安全運行，資料處理設備會定期獲取監測參數（例如CPU的電壓與溫度）的觀測值，根據獲取的資料對資料處理設備進行管理和控制。例如，當CPU的電壓超過門限值時，資料處理設備會切斷電源並向遠端終端發出警報。然而，資料處理設備獲取的觀測值中可能存在錯誤值，這些錯誤值將影響資料處理設備執行正確操作。In order to ensure the safe operation of the data processing equipment (such as the server), the data processing equipment periodically acquires observation values of monitoring parameters (such as CPU voltage and temperature), and manages and controls the data processing equipment according to the acquired data. For example, when the voltage of the CPU exceeds the threshold, the data processing device turns off the power and issues an alarm to the remote terminal. However, there may be erroneous values in the observations obtained by the data processing device, which will affect the data processing device to perform correct operations.
鑒於以上內容，有必要提供一種排除錯誤觀測值的系統及方法，能夠檢測並清除觀測值中的錯誤值。In view of the above, it is necessary to provide a system and method for eliminating erroneous observations that can detect and clear erroneous values in the observations.
一種排除錯誤觀測值的系統，運行於資料處理設備中，該系統包括：獲取模組，用於定期獲取監測參數的觀測值；預測模組，用於計算觀測值的預測值；判斷模組，用於判斷觀測值是否在其預測值的允許偏差範圍內；儲存模組，用於當觀測值在其預測值的允許偏差範圍內時，將觀測值作為真實值進行儲存；及驗證模組，用於當觀測值不在其預測值的允許偏差範圍內時，獲取觀測值的臨近值並根據觀測值計算其臨近值的預測值，判斷臨近值是否在其預測值的允許偏差範圍內，若臨近值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存，否則，若臨近值不在其預測值的允許偏差範圍內，則將觀測值作為錯誤值而捨棄。A system for eliminating erroneous observations, running in a data processing device, the system comprising: an acquisition module for periodically acquiring observation values of monitoring parameters; a prediction module for calculating a predicted value of the observation value; a determination module, It is used to determine whether the observed value is within the allowable deviation range of the predicted value; the storage module is configured to store the observed value as a true value when the observed value is within the allowable deviation range of the predicted value; and the verification module, When the observed value is not within the allowable deviation range of the predicted value, obtain the adjacent value of the observed value and calculate the predicted value of the adjacent value according to the observed value, and determine whether the adjacent value is within the allowable deviation range of the predicted value, if adjacent If the value is within the allowable deviation of its predicted value, the observed value is stored as the true value. Otherwise, if the adjacent value is not within the allowable deviation of the predicted value, the observed value is discarded as the error value.
一種排除錯誤觀測值的方法，執行於資料處理設備中，該方法包括步驟：定期獲取監測參數的觀測值；計算觀測值的預測值；判斷觀測值是否在其預測值的允許偏差範圍內；若觀測值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存；若觀測值不在其預測值的允許偏差範圍內，則獲取觀測值的臨近值；根據觀測值計算其臨近值的預測值；判斷臨近值是否在其預測值的允許偏差範圍內；及若臨近值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存，否則，若臨近值不在其預測值的允許偏差範圍內，則將觀測值作為錯誤值而捨棄。A method for eliminating erroneous observations is performed in a data processing device, the method comprising the steps of: periodically acquiring observation values of the monitoring parameters; calculating a predicted value of the observed values; determining whether the observed values are within an allowable deviation range of the predicted values; If the observed value is within the allowable deviation range of its predicted value, the observed value is stored as the true value; if the observed value is not within the allowable deviation range of the predicted value, the adjacent value of the observed value is obtained; and the adjacent value is calculated according to the observed value The predicted value; whether the adjacent value is within the allowable deviation range of its predicted value; and if the adjacent value is within the allowable deviation range of the predicted value, the observed value is stored as a true value; otherwise, if the adjacent value is not in its prediction Within the allowable deviation of the value, the observation is discarded as an error value.
本發明對數據處理設備的監測參數進行預測，判斷觀測值是否在其預測值的允許偏差範圍內，從而檢測出錯誤觀測值，避免了錯誤觀測值影響資料處理設備執行正確操作。The invention predicts the monitoring parameters of the data processing device, determines whether the observed value is within the allowable deviation range of the predicted value, thereby detecting the erroneous observation value, and avoids that the erroneous observation value affects the data processing device to perform the correct operation.
參閱圖1所示，係本發明排除錯誤觀測值的系統較佳實施例的應用環境示意圖。所述排除錯誤觀測值的系統10運行於資料處理設備11中。該資料處理設備11利用資料獲取設備12（例如溫度感測器、電壓表）定期獲取資料處理設備11的監測參數的觀測值，根據獲取的資料對資料處理設備11進行管理和控制。在本實施例中，所述監測參數包括電壓和溫度。例如，資料處理設備11每隔1秒獲取一次CPU的電壓的觀測值，當CPU的電壓超過門限值時切斷電源並向遠端終端發出警報。資料處理設備11獲取的觀測值中可能存在錯誤值，該錯誤值將影響資料處理設備11執行正確操作。運行所述排除錯誤觀測值的系統10，能夠檢測並清除觀測值中的錯誤值。在本實施例中，所述資料處理設備11為伺服器，所述排除錯誤觀測值的系統10運行於該伺服器的基板管理控制器中。Referring to Figure 1, there is shown a schematic diagram of an application environment of a preferred embodiment of the system for eliminating erroneous observations. The system 10 for eliminating erroneous observations runs in the data processing device 11. The data processing device 11 periodically acquires observation values of the monitoring parameters of the data processing device 11 by using the data acquisition device 12 (for example, a temperature sensor, a voltmeter), and manages and controls the data processing device 11 based on the acquired data. In this embodiment, the monitoring parameters include voltage and temperature. For example, the data processing device 11 acquires an observation value of the voltage of the CPU every one second, and turns off the power and issues an alarm to the remote terminal when the voltage of the CPU exceeds the threshold. There may be an erroneous value among the observations acquired by the data processing device 11, which will affect the data processing device 11 to perform the correct operation. The system 10 that operates the excluded erroneous observations is capable of detecting and clearing erroneous values in the observed values. In this embodiment, the data processing device 11 is a server, and the system 10 for eliminating erroneous observations runs in the baseboard management controller of the server.
參閱圖2所示，係圖1中排除錯誤觀測值的系統的功能模組圖。所述排除錯誤觀測值的系統10包括獲取模組200、預測模組210、判斷模組220、儲存模組230及驗證模組240。Referring to Figure 2, a functional module diagram of the system for eliminating erroneous observations in Figure 1 is shown. The system 10 for eliminating erroneous observations includes an acquisition module 200, a prediction module 210, a determination module 220, a storage module 230, and a verification module 240.
所述獲取模組200用於定期獲取資料處理設備11的監測參數的觀測值。如前所述，所述獲取模組200利用資料獲取設備12來獲取監測參數的觀測值，所述監測參數包括溫度與電壓。例如，獲取模組200每隔1秒獲取一次CPU的電壓的觀測值。The acquisition module 200 is configured to periodically acquire observation values of monitoring parameters of the data processing device 11. As described above, the acquisition module 200 uses the data acquisition device 12 to acquire observation values of the monitoring parameters, including temperature and voltage. For example, the acquisition module 200 acquires an observation value of the voltage of the CPU every one second.
所述預測模組210用於計算觀測值的預測值。在本實施例中，預測模組210採用指數平滑法計算觀測值的預測值。例如，預測模組210採用一次指數平滑法計算觀測值的預測值，所述一次指數平滑法的公式為：，其中α是平滑常數，取值在0到1之間，是本期的預測值，是上一期的預測值，是上一期的觀測值。所述預測模組210還可以採用其他的預測演算法（例如移動平均法）計算觀測值的預測值。The prediction module 210 is configured to calculate a predicted value of the observed value. In the present embodiment, the prediction module 210 calculates the predicted value of the observed value by using an exponential smoothing method. For example, the prediction module 210 calculates a predicted value of the observed value by using an exponential smoothing method, and the formula of the first exponential smoothing method is: , where α is a smoothing constant, and the value is between 0 and 1, Is the predicted value of this period, Is the predicted value of the previous period, It is the observation of the previous period. The prediction module 210 may also use other prediction algorithms (such as a moving average method) to calculate a predicted value of the observed value.
所述判斷模組220用於判斷觀測值是否在其預測值的允許偏差範圍內。在本實施例中，對於觀測值，以其預測值正負偏差一定百分比或者一定數值作為其預測值的允許偏差範圍。例如，以預測值正負偏差百分之五作為預測值的允許偏差範圍，若預測值為1.5V，則預測值的允許偏差範圍為1.5*（1-5%）V至1.5*（1+5%）V，即1.425V~1.575V。又如，以預測值正負偏差0.1V作為預測值的允許偏差範圍，若預測值為1.5V，則預測值的允許偏差範圍為（1.5-0.1）V至（1.5+0.1）V，即1.4V~1.6V。The determining module 220 is configured to determine whether the observed value is within an allowable deviation range of its predicted value. In the present embodiment, for the observation value, a certain percentage of the positive or negative deviation of the predicted value or a certain value is used as the allowable deviation range of the predicted value. For example, if the predicted value is 1.5V, the allowable deviation range of the predicted value is 1.5*(1-5%)V to 1.5*(1+5). %)V, which is 1.425V~1.575V. For example, if the predicted value is 1.5V, the allowable deviation range of the predicted value is (1.5-0.1)V to (1.5+0.1)V, that is, 1.4V. ~1.6V.
所述儲存模組230用於當觀測值在其預測值的允許偏差範圍內時，將觀測值作為真實值進行儲存，用以對資料處理設備11進行管理和控制。例如，若觀測值為1.45V，其預測值的允許偏差範圍為1.425V~1.575V，則觀測值在其預測值的允許偏差範圍內，儲存模組230將該觀測值作為真實值進行儲存。The storage module 230 is configured to store the observed value as a real value when the observed value is within the allowable deviation range of the predicted value, for managing and controlling the data processing device 11. For example, if the observed value is 1.45V and the allowable deviation of the predicted value ranges from 1.425V to 1.575V, the storage module 230 stores the observed value as a true value within the allowable deviation range of the predicted value.
所述驗證模組240用於當觀測值不在其預測值的允許偏差範圍內時，獲取觀測值的臨近值並根據觀測值計算其臨近值的預測值。所述觀測值的臨近值是指在觀測值之後間隔較短時間（例如50毫秒）測得的監測參數的數值。在本實施例中，驗證模組240間隔50毫秒連續兩次獲取觀測值的臨近值，並且採用與計算觀測值的預測值相同的方法（例如指數平滑法）來計算臨近值的預測值。驗證模組240判斷臨近值是否在其預測值的允許偏差範圍內，若臨近值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存，用以對資料處理設備11進行管理和控制，否則，若臨近值不在其預測值的允許偏差範圍內，則將觀測值作為錯誤值而捨棄。在本實施例中，對於臨近值，以其預測值正負偏差一定百分比或者一定數值作為其預測值的允許偏差範圍。The verification module 240 is configured to acquire a neighboring value of the observed value when the observed value is not within the allowable deviation range of the predicted value, and calculate a predicted value of the adjacent value according to the observed value. The proximity value of the observation refers to the value of the monitoring parameter measured at a short interval (for example, 50 milliseconds) after the observation. In the present embodiment, the verification module 240 acquires the adjacent values of the observations twice in succession at intervals of 50 milliseconds, and calculates the predicted values of the adjacent values by the same method as calculating the predicted values of the observations (for example, exponential smoothing). The verification module 240 determines whether the adjacent value is within the allowable deviation range of the predicted value. If the adjacent value is within the allowable deviation range of the predicted value, the observed value is stored as a real value for managing the data processing device 11. And control, otherwise, if the neighboring value is not within the allowable deviation of its predicted value, the observed value is discarded as the wrong value. In the present embodiment, for the adjacent value, a certain percentage of the positive or negative deviation of the predicted value or a certain value is used as the allowable deviation range of the predicted value.
參閱圖3所示，係本發明排除錯誤觀測值的方法較佳實施例的流程圖。Referring to Figure 3, there is shown a flow chart of a preferred embodiment of the method of the present invention for eliminating erroneous observations.
步驟S301，獲取模組200定期獲取資料處理設備11的監測參數的觀測值。在本實施例中，所述獲取模組200利用資料獲取設備12（例如溫度感測器、電壓表）來獲取監測參數的觀測值，所述監測參數包括溫度與電壓。例如，獲取模組200每隔1秒獲取一次CPU的電壓的觀測值。In step S301, the acquisition module 200 periodically acquires the observation value of the monitoring parameter of the data processing device 11. In this embodiment, the acquisition module 200 uses the data acquisition device 12 (eg, a temperature sensor, a voltmeter) to obtain an observation value of the monitoring parameter, and the monitoring parameter includes temperature and voltage. For example, the acquisition module 200 acquires an observation value of the voltage of the CPU every one second.
步驟S302，預測模組210計算觀測值的預測值。在本實施例中，預測模組210採用指數平滑法計算觀測值的預測值。例如，預測模組210採用一次指數平滑法計算觀測值的預測值，所述一次指數平滑法的公式為：，其中α是平滑常數，取值在0到1之間，是本期的預測值，是上一期的預測值，是上一期的觀測值。所述預測模組210還可以採用其他的預測演算法（例如移動平均法）計算觀測值的預測值。In step S302, the prediction module 210 calculates a predicted value of the observed value. In the present embodiment, the prediction module 210 calculates the predicted value of the observed value by using an exponential smoothing method. For example, the prediction module 210 calculates a predicted value of the observed value by using an exponential smoothing method, and the formula of the first exponential smoothing method is: , where α is a smoothing constant, and the value is between 0 and 1, Is the predicted value of this period, Is the predicted value of the previous period, It is the observation of the previous period. The prediction module 210 may also use other prediction algorithms (such as a moving average method) to calculate a predicted value of the observed value.
步驟S303，判斷模組220判斷觀測值是否在其預測值的允許偏差範圍內。在本實施例中，對於觀測值，以其預測值正負偏差一定百分比或者一定數值作為其預測值的允許偏差範圍。例如，以預測值正負偏差百分之五作為預測值的允許偏差範圍，若預測值為1.5V，則預測值的允許偏差範圍為1.5*（1-5%）V至1.5*（1+5%）V，即1.425V~1.575V。又如，以預測值正負偏差0.1V作為預測值的允許偏差範圍，若預測值為1.5V，則預測值的允許偏差範圍為（1.5-0.1）V至（1.5+0.1）V，即1.4V~1.6V。In step S303, the determining module 220 determines whether the observed value is within the allowable deviation range of the predicted value. In the present embodiment, for the observation value, a certain percentage of the positive or negative deviation of the predicted value or a certain value is used as the allowable deviation range of the predicted value. For example, if the predicted value is 1.5V, the allowable deviation range of the predicted value is 1.5*(1-5%)V to 1.5*(1+5). %)V, which is 1.425V~1.575V. For example, if the predicted value is 1.5V, the allowable deviation range of the predicted value is (1.5-0.1)V to (1.5+0.1)V, that is, 1.4V. ~1.6V.
若觀測值在其預測值的允許偏差範圍內，步驟S304，儲存模組230將觀測值作為真實值進行儲存，用以對資料處理設備11進行管理和控制。例如，若觀測值為1.45V，其預測值的允許偏差範圍為1.425V~1.575V，則觀測值在其預測值的允許偏差範圍內，儲存模組230將該觀測值作為真實值進行儲存。If the observed value is within the allowable deviation range of the predicted value, the storage module 230 stores the observed value as a real value for managing and controlling the data processing device 11 in step S304. For example, if the observed value is 1.45V and the allowable deviation of the predicted value ranges from 1.425V to 1.575V, the storage module 230 stores the observed value as a true value within the allowable deviation range of the predicted value.
若觀測值不在其預測值的允許偏差範圍內，步驟S305，驗證模組240獲取觀測值的臨近值。所述觀測值的臨近值是指在觀測值之後間隔較短時間（例如50毫秒）測得的監測參數的數值。在本實施例中，驗證模組240間隔50毫秒連續兩次獲取觀測值的臨近值。If the observed value is not within the allowable deviation range of the predicted value, the verification module 240 acquires the adjacent value of the observed value in step S305. The proximity value of the observation refers to the value of the monitoring parameter measured at a short interval (for example, 50 milliseconds) after the observation. In this embodiment, the verification module 240 acquires the adjacent values of the observations twice in succession at intervals of 50 milliseconds.
步驟S306，驗證模組240根據觀測值計算其臨近值的預測值。在本實施例中，採用與計算觀測值的預測值相同的方法（例如指數平滑法）來計算臨近值的預測值。In step S306, the verification module 240 calculates a predicted value of its neighboring value based on the observed value. In the present embodiment, the same value as the predicted value of the calculated observation value (for example, exponential smoothing method) is used to calculate the predicted value of the adjacent value.
步驟S307，驗證模組240判斷臨近值是否在其預測值的允許偏差範圍內。在本實施例中，對於臨近值，以其預測值正負偏差一定百分比或者一定數值作為其預測值的允許偏差範圍。In step S307, the verification module 240 determines whether the adjacent value is within the allowable deviation range of its predicted value. In the present embodiment, for the adjacent value, a certain percentage of the positive or negative deviation of the predicted value or a certain value is used as the allowable deviation range of the predicted value.
如果臨近值在其預測值的允許偏差範圍內，步驟S308，驗證模組240將觀測值作為真實值進行儲存，用以對資料處理設備11進行管理和控制。If the proximity value is within the allowable deviation range of its predicted value, the verification module 240 stores the observation value as a real value for managing and controlling the data processing device 11 in step S308.
否則，若臨近值不在其預測值的允許偏差範圍內，步驟S308，驗證模組240將觀測值作為錯誤值而捨棄。Otherwise, if the proximity value is not within the allowable deviation range of its predicted value, the verification module 240 discards the observation value as an error value in step S308.
綜上所述，本發明符合發明專利要件，爰依法提出專利申請。惟，以上所述者僅為本發明之較佳實施例，本發明之範圍並不以上述實施例為限，舉凡熟悉本案技藝之人士援依本發明之精神所作之等效修飾或變化，皆應涵蓋於以下申請專利範圍內。In summary, the present invention complies with the requirements of the invention patent and submits a patent application according to law. The above is only the preferred embodiment of the present invention, and the scope of the present invention is not limited to the above-described embodiments, and equivalent modifications or variations made by those skilled in the art in light of the spirit of the present invention are It should be covered by the following patent application.
10．．．排除錯誤觀測值的系統10. . . System for eliminating erroneous observations
11．．．資料處理設備11. . . Data processing equipment
12．．．資料獲取設備12. . . Data acquisition equipment
200．．．獲取模組200. . . Get module
210．．．預測模組210. . . Prediction module
220．．．判斷模組220. . . Judging module
230．．．儲存模組230. . . Storage module
240．．．驗證模組240. . . Verification module
圖1係本發明排除錯誤觀測值的系統較佳實施例的應用環境示意圖。1 is a schematic diagram of an application environment of a preferred embodiment of a system for eliminating erroneous observations of the present invention.
圖2係圖1中排除錯誤觀測值的系統的功能模組圖。Figure 2 is a functional block diagram of the system for eliminating erroneous observations in Figure 1.
圖3係本發明排除錯誤觀測值的方法較佳實施例的流程圖。3 is a flow diagram of a preferred embodiment of the method of the present invention for eliminating erroneous observations.
10．．．排除錯誤觀測值的系統10. . . System for eliminating erroneous observations
200．．．獲取模組200. . . Get module
210．．．預測模組210. . . Prediction module
220．．．判斷模組220. . . Judging module
230．．．儲存模組230. . . Storage module
240．．．驗證模組240. . . Verification module
Claims (10)
獲取模組，用於定期獲取監測參數的觀測值；
預測模組，用於計算觀測值的預測值；
判斷模組，用於判斷觀測值是否在其預測值的允許偏差範圍內；
儲存模組，用於當觀測值在其預測值的允許偏差範圍內時，將觀測值作為真實值進行儲存；及
驗證模組，用於當觀測值不在其預測值的允許偏差範圍內時，獲取觀測值的臨近值並根據觀測值計算其臨近值的預測值，判斷臨近值是否在其預測值的允許偏差範圍內，若臨近值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存，否則，若臨近值不在其預測值的允許偏差範圍內，則將觀測值作為錯誤值而捨棄。A system for eliminating erroneous observations, operating in a data processing device, the system comprising:
Obtaining a module for periodically obtaining observations of monitoring parameters;
a prediction module for calculating a predicted value of the observed value;
a determining module for determining whether the observed value is within an allowable deviation range of the predicted value thereof;
a storage module for storing the observed value as a true value when the observed value is within the allowable deviation range of the predicted value; and a verification module for when the observed value is out of the allowable deviation range of the predicted value, Obtain the adjacent value of the observed value and calculate the predicted value of the adjacent value according to the observed value to determine whether the adjacent value is within the allowable deviation range of the predicted value. If the adjacent value is within the allowable deviation range of the predicted value, the observed value is taken as The actual value is stored. Otherwise, if the adjacent value is not within the allowable deviation of its predicted value, the observed value is discarded as an error value.
定期獲取監測參數的觀測值；
計算觀測值的預測值；
判斷觀測值是否在其預測值的允許偏差範圍內；
若觀測值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存；
若觀測值不在其預測值的允許偏差範圍內，則獲取觀測值的臨近值；
根據觀測值計算其臨近值的預測值；
判斷臨近值是否在其預測值的允許偏差範圍內；及
若臨近值在其預測值的允許偏差範圍內，則將觀測值作為真實值進行儲存，否則，若臨近值不在其預測值的允許偏差範圍內，則將觀測值作為錯誤值而捨棄。A method for eliminating erroneous observations, performed in a data processing device, the method comprising the steps of:
Obtain observations of monitoring parameters on a regular basis;
Calculate the predicted value of the observed value;
Determine whether the observed value is within the allowable deviation of its predicted value;
If the observed value is within the allowable deviation of its predicted value, the observed value is stored as a true value;
Obtaining an adjacent value of the observed value if the observed value is not within the allowable deviation of its predicted value;
Calculate the predicted value of its neighboring value based on the observed value;
Determine whether the adjacent value is within the allowable deviation range of its predicted value; and if the adjacent value is within the allowable deviation range of its predicted value, store the observed value as a true value; otherwise, if the adjacent value is not within the allowable deviation of its predicted value Within the scope, the observations are discarded as error values.
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| TW099146261A TWI479311B (en) | 2010-12-28 | 2010-12-28 | System and method for eliminating wrong observed values |
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| TW099146261A TWI479311B (en) | 2010-12-28 | 2010-12-28 | System and method for eliminating wrong observed values |
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| TWI479311B true TWI479311B (en) | 2015-04-01 |
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| US4719642A (en) * | 1985-02-27 | 1988-01-12 | Scientific Atlanta, Inc. | Error detection and concealment using predicted signal values |
| US5222065A (en) * | 1989-07-15 | 1993-06-22 | Bodenseewerk Geratetechnik Gmbh | Device for generating measuring signals with a plurality of redundantly provided sensors |
| US6625527B1 (en) * | 1999-02-18 | 2003-09-23 | Continental Teves Ag & Co. Ohg | Sensor system with monitoring device |
| TW200408936A (en) * | 2002-05-29 | 2004-06-01 | Tokyo Electron Ltd | Method and apparatus for monitoring tool performance |
| US7228249B2 (en) * | 2002-11-19 | 2007-06-05 | General Motors Corporation | Methods and apparatus for determining the condition of a sensor and identifying the failure thereof |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4719642A (en) * | 1985-02-27 | 1988-01-12 | Scientific Atlanta, Inc. | Error detection and concealment using predicted signal values |
| US5222065A (en) * | 1989-07-15 | 1993-06-22 | Bodenseewerk Geratetechnik Gmbh | Device for generating measuring signals with a plurality of redundantly provided sensors |
| US6625527B1 (en) * | 1999-02-18 | 2003-09-23 | Continental Teves Ag & Co. Ohg | Sensor system with monitoring device |
| TW200408936A (en) * | 2002-05-29 | 2004-06-01 | Tokyo Electron Ltd | Method and apparatus for monitoring tool performance |
| US7228249B2 (en) * | 2002-11-19 | 2007-06-05 | General Motors Corporation | Methods and apparatus for determining the condition of a sensor and identifying the failure thereof |
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| TW201227283A (en) | 2012-07-01 |
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