JPH07294282A - Method for removing noise from measurement - Google Patents

Method for removing noise from measurement

Info

Publication number
JPH07294282A
JPH07294282A JP6114325A JP11432594A JPH07294282A JP H07294282 A JPH07294282 A JP H07294282A JP 6114325 A JP6114325 A JP 6114325A JP 11432594 A JP11432594 A JP 11432594A JP H07294282 A JPH07294282 A JP H07294282A
Authority
JP
Japan
Prior art keywords
value
noise
measurement
data
smoothed
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
JP6114325A
Other languages
Japanese (ja)
Inventor
Akimasa Mega
章正 目賀
Toshinobu Aki
年信 安芸
Akinori Kiyofuji
章典 清藤
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shimadzu Corp
Original Assignee
Shimadzu Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shimadzu Corp filed Critical Shimadzu Corp
Priority to JP6114325A priority Critical patent/JPH07294282A/en
Publication of JPH07294282A publication Critical patent/JPH07294282A/en
Pending legal-status Critical Current

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  • Indication And Recording Devices For Special Purposes And Tariff Metering Devices (AREA)
  • Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Filters That Use Time-Delay Elements (AREA)

Abstract

PURPOSE:To reduce noise as much as possible without obscuring the variation in the amount of an object itself. CONSTITUTION:A polynomial fitting method is employed (step S8, S9) when a value sigma<2>/r, obtained by dividing the variance sigma<2> of measurements taken during a predetermined section by the mean value (r) of the measurements, exceeds a predetermined threshold value otherwise a simple moving average method exhibiting higher noise reduction effect is employed (step S4, S7).

Description

【発明の詳細な説明】Detailed Description of the Invention

【0001】[0001]

【産業上の利用分野】本発明は、例えば蛍光分析装置等
の測定装置で採取される測定値データからノイズを除去
するための方法に関する。
BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for removing noise from measured value data collected by a measuring device such as a fluorescence analyzer.

【0002】[0002]

【従来の技術】一般に、測定装置の感度を高めるほど、
測定装置で得られる測定値はノイズに影響されやすくな
る。例えば、大気中の汚染物質であるSO2の濃度を測
定するためのSO2濃度測定装置では、試料ガスに紫外
線をパルス照射し、励起されたSO2分子が放出する蛍
光を検出して試料ガス中のSO2成分の濃度を検出す
る。ここで、試料ガス中のSO2成分の濃度が低く、蛍
光が非常に微弱である場合には、蛍光検出器における光
電変換過程そのものの確率的性質が測定値をばらつかせ
る。
2. Description of the Related Art Generally, the higher the sensitivity of a measuring device,
The measured value obtained by the measuring device is easily affected by noise. For example, in a SO 2 concentration measuring device for measuring the concentration of SO 2 which is a pollutant in the air, the sample gas is pulse-irradiated with ultraviolet rays and the fluorescence emitted by the excited SO 2 molecule is detected to detect the sample gas. The concentration of the SO 2 component in the sample is detected. Here, when the concentration of the SO 2 component in the sample gas is low and the fluorescence is very weak, the stochastic property of the photoelectric conversion process itself in the fluorescence detector causes the measured values to vary.

【0003】このようなノイズ成分を含む信号から真の
測定値を得るために、従来より各種のノイズ除去方法が
考えられてきた。近年、デジタルデータ処理のための素
子の高速化及び低価格化が進んできた結果、測定装置か
らの信号を一定時間間隔でサンプリングしてデジタルデ
ータに変換した後、各種データ処理を行なうことにより
ノイズを除去する方法が主流となっている。そして、デ
ジタルデータ処理によるノイズ除去法には、採取データ
をそのままの形で平滑化処理する移動平均法と、フーリ
エ変換を用いて一旦周波数領域に変換してから処理する
周波数領域法とがある。
In order to obtain a true measurement value from a signal containing such a noise component, various noise removing methods have been conventionally considered. In recent years, as elements for digital data processing have become faster and cheaper, the signal from the measuring device is sampled at fixed time intervals and converted into digital data, and then various data processing is performed to reduce noise. The method of removing is becoming mainstream. The noise removal method based on digital data processing includes a moving average method that smoothes the sampled data as it is and a frequency domain method that transforms the sampled data into a frequency domain once using Fourier transform and then processes.

【0004】移動平均法は、求めたい平滑化測定値y
(i)の前後の(2m+1)個の採取データx(i+
j)(j=−m,…,0,…,+m)の各々に重みw
(i)(i=−m,…,0,…,+m)を与え、 y(i)=(1/W)・{Σ(j=−m〜m)w(j)・
x(i+j)} W=Σ(j=−m〜m)w(j) として平滑化測定値y(i)を求めるものである。この
重み関数w(j)をjに拘らず一定とする場合を単純移
動平均法と呼ぶ。また、測定値中の信号波形が部分的に
多項式曲線により近似できると仮定して、この曲線への
適合を行なうようにw(j)を設定する方法を多項式適
合法と呼ぶ。
The moving average method uses the smoothed measurement value y to be obtained.
(2m + 1) collected data x (i +) before and after (i)
j) Weight w for each of (j = -m, ..., 0, ..., + m)
(I) (i = -m, ..., 0, ..., + m) is given, and y (i) = (1 / W) · {Σ (j = −m to m) w (j) ·
x (i + j)} W = Σ (j = -m to m) w (j) to obtain the smoothed measurement value y (i). A case where the weighting function w (j) is constant regardless of j is called a simple moving average method. Further, a method of setting w (j) so as to fit the curve assuming that the signal waveform in the measured value can be partially approximated by the polynomial curve is called a polynomial fitting method.

【0005】[0005]

【発明が解決しようとする課題】単純移動平均法はノイ
ズを低減させる効果は大きいが、信号自体を歪ませ、測
定対象量自体の変化を隠してしまうおそれがある。一
方、多項式適合法は信号を歪ませることは少ないが、単
純移動平均法に比べノイズ低減効果が小さいという性質
を持つ。
Although the simple moving average method has a great effect of reducing noise, it may distort the signal itself and hide the change in the quantity to be measured itself. On the other hand, the polynomial fitting method hardly distorts the signal, but has a property that the noise reduction effect is smaller than that of the simple moving average method.

【0006】本発明はこのような課題を解決するために
成されたものであり、その目的とするところは、ノイズ
を最大限に低減し、しかも、測定対象量自体の変化を隠
すことのないノイズ除去方法を提供することにある。
The present invention has been made in order to solve such a problem, and an object thereof is to reduce noise to the maximum extent and not to hide the change in the quantity to be measured itself. It is to provide a noise removing method.

【0007】[0007]

【課題を解決するための手段】上記課題を解決するため
に成された本発明に係る測定値のノイズ除去方法は、所
定の長さの区間内に採取された測定値の分散を該区間内
の測定値の平均値で除した値が所定の閾値を超えるとき
は第1のノイズ除去法を使用し、所定の閾値以下のとき
は第1のノイズ除去法よりもノイズ低減効果の大きい第
2のノイズ除去法を使用することを特徴としている。
A method for removing noise from a measured value according to the present invention, which has been made to solve the above-mentioned problems, provides a method of measuring the variance of measured values within a section of a predetermined length within the section. The first noise removal method is used when the value divided by the average value of the measured values exceeds the predetermined threshold value. It is characterized by using the noise removal method of.

【0008】[0008]

【作用】確率的現象に関する場合等の多くの測定におい
ては、測定値のばらつきはポアソン分布 P(λ)=(λk/k!)exp(-λ) (ただし、k=0,1,2,…)に従うと考えられる。
ポアソン分布では平均値m=λ、分散σ2=λであるた
め、σ2/mの値は常に一定(=1)である。測定条件
が一定である間、ノイズ成分の大きさは一定であると考
えられるが、測定対象量自体が変化し、しかもその変化
が急激である場合には、測定対象量の急激な変化がノイ
ズによるばらつきよりも大きくσ2に寄与するようにな
り、σ2/mの値が増加する。従って、σ2/mの値が所
定値よりも大きくなったときは、測定対象量自体に変化
が生じていることであると考えられるため、ノイズ除去
法が測定対象量自体の変化を隠すことがないように、ノ
イズ低減効果の緩やかな第1のノイズ除去法を使用す
る。一方、σ2/mの値が所定値以下であるときは、測
定対象量自体の変化は無い、或いは緩やかであると考え
られるため、ノイズ低減効果の大きい第2のノイズ除去
法を使用することにより、測定対象量の真の値により近
い測定値を得ることができるようになる。
In many measurements such as those relating to stochastic phenomena, the dispersion of the measured values is the Poisson distribution P (λ) = (λ k / k!) Exp (-λ) (where k = 0, 1, 2 , ...)
In the Poisson distribution, the average value m = λ and the variance σ 2 = λ, so the value of σ 2 / m is always constant (= 1). It is considered that the magnitude of the noise component is constant while the measurement conditions are constant.However, if the measured quantity itself changes and the change is abrupt, a sudden change in the measured quantity causes noise. The value of σ 2 / m increases, as it contributes to σ 2 more than the variation due to. Therefore, when the value of σ 2 / m becomes larger than the predetermined value, it is considered that the measurement target amount itself has changed, and therefore the noise removal method hides the change of the measurement target amount itself. Therefore, the first denoising method with a gentle noise reduction effect is used so that there is no noise. On the other hand, when the value of σ 2 / m is less than or equal to the predetermined value, it is considered that there is no change or a gradual change in the amount to be measured itself. Therefore, use the second noise removal method that has a large noise reduction effect. This makes it possible to obtain a measurement value that is closer to the true value of the measurement target amount.

【0009】[0009]

【実施例】本発明に係る方法を使って測定値の平滑化処
理を行なう蛍光式SO2濃度測定装置を図1により説明
する。キセノンランプ11から放出されるパルス光のう
ち、SO2の励起に最適な波長域を光学フィルタ12に
より選択的に透過して、蛍光室(フローセル)13内の
試料ガスに照射する。これにより励起された試料ガス中
のSO2は、その基底状態に戻る際に、励起光よりもや
や長い波長の蛍光を放出する。光学フィルタ14はこの
蛍光の波長域のみを選択して通過させ、光電子増倍管1
5はその蛍光の強度を検出する。光電子増倍管15の検
出信号はデータ処理部16に送られ、そこで後述の平滑
化処理が行なわれる。図2に示すように、データ処理部
16はCPU22、ROM24、RAM25等を備えた
マイコンにより構成され、A/D変換器21を介して光
電子増倍管15から入力される原測定値を平滑化処理
し、インタフェイス23を介してCRT、LCD、レコ
ーダ等の出力装置20に平滑化データを出力する。
DESCRIPTION OF THE PREFERRED EMBODIMENTS A fluorescent SO 2 concentration measuring apparatus for smoothing measured values using the method according to the present invention will be described with reference to FIG. Of the pulsed light emitted from the xenon lamp 11, a wavelength region most suitable for SO 2 excitation is selectively transmitted by the optical filter 12, and the sample gas in the fluorescent chamber (flow cell) 13 is irradiated with the sample gas. The SO 2 in the sample gas thus excited emits fluorescence having a wavelength slightly longer than the excitation light when returning to its ground state. The optical filter 14 selects and passes only the wavelength region of this fluorescence, and the photomultiplier tube 1
5 detects the intensity of the fluorescence. The detection signal of the photomultiplier tube 15 is sent to the data processing unit 16 where the smoothing process described later is performed. As shown in FIG. 2, the data processing unit 16 is composed of a microcomputer including a CPU 22, a ROM 24, a RAM 25, etc., and smoothes the original measurement value input from the photomultiplier tube 15 via the A / D converter 21. The processed data is output via the interface 23 to the output device 20 such as a CRT, LCD, or recorder.

【0010】CPU22の行なう平滑化処理を図3のフ
ローチャートにより説明する。CPU22は、A/D変
換器21でサンプリングされたデータを受け取った(ス
テップS1)後、まずそのデータをRAM25に記憶さ
せる(ステップS2)。そして、RAM25から、今回
のデータ迄の所定個数のデータを読み出し(ステップS
3)、その平均値(区間平均)r及び分散(区間分散)
σ2を算出する(ステップS4、S5)。次に、区間分
散σ2を区間平均rで除した値σ2/rが所定の閾値aを
超えているか否かを判定する(ステップS6)。σ2
r≦aである場合には、ステップS4で算出した区間平
均r(これはすなわち、単純移動平均である)を平滑化
測定値sとして(ステップS7)、平滑化測定値sを出
力装置20に出力する(ステップS10)。σ2/r>
aである場合には、ステップS3で読み出したデータに
対して多項式適合法による平滑化演算を行ない、平滑化
された測定値pを算出する(ステップS8)。そして、
この多項式適合法による平滑化値pを平滑化測定値sと
して(ステップS9)出力装置20に出力する(ステッ
プS10)。従って、図3の例の場合、ステップS4で
使用する単純移動平均法が第2のノイズ除去法であり、
ステップS8で使用する多項式適合法が第1のノイズ除
去法である。ステップS10で平滑化値sを出力した
後、ステップS1に戻ってA/D変換器21より次のデ
ータを取得する。
The smoothing process performed by the CPU 22 will be described with reference to the flowchart of FIG. After receiving the data sampled by the A / D converter 21 (step S1), the CPU 22 first stores the data in the RAM 25 (step S2). Then, a predetermined number of data up to the current data is read from the RAM 25 (step S
3), its average value (interval average) r and variance (interval variance)
σ 2 is calculated (steps S4 and S5). Next, it is determined whether or not the value σ 2 / r obtained by dividing the section variance σ 2 by the section average r exceeds a predetermined threshold value a (step S6). σ 2 /
If r ≦ a, the section average r calculated in step S4 (that is, a simple moving average) is set as the smoothed measurement value s (step S7), and the smoothed measurement value s is output to the output device 20. Output (step S10). σ 2 / r>
If it is a, the data read out in step S3 is smoothed by the polynomial fitting method to calculate the smoothed measurement value p (step S8). And
The smoothed value p obtained by this polynomial fitting method is output as the smoothed measured value s (step S9) to the output device 20 (step S10). Therefore, in the case of the example of FIG. 3, the simple moving average method used in step S4 is the second noise removal method,
The polynomial fitting method used in step S8 is the first noise removal method. After outputting the smoothed value s in step S10, the process returns to step S1 to acquire the next data from the A / D converter 21.

【0011】SO2を含まない試料ガスを本実施例のS
2濃度測定装置10で測定したときの、光電子増倍管
15から出力される信号をA/D変換したままのデータ
を図4に示す。ただし、キセノンランプ11は毎秒10
回点灯させており、図4のグラフは3秒毎の光電子増倍
管15の出力の平均値を1点としてプロットしたもので
ある。試料ガスにはSO2が含まれていないため、図4
に現われているものは全てノイズである。このデータに
対してσ2/r(ただし、r、σ2算出区間内のデータ個
数は40個)を算出した結果が図5のグラフである。σ
2/rの値はほとんど変化しておらず、その値は0.0
1程度と非常に小さい。本実施例では閾値aを1とする
ため、図4のデータの場合、全域でσ2/r<aとなっ
ている。従って、上記の通り、単純移動平均法により算
出した値rを平滑化値sとすることになり、図6に示す
ように、ノイズが大きく低減された測定値(実線)カー
ブが得られる。なお、図6には参考のために、多項式適
合法で算出した値を平滑化値とした場合のカーブを破線
で示したが、本発明により、十分なノイズ低減効果が得
られていることがわかる。
A sample gas containing no SO 2 was used as the S gas in this embodiment.
FIG. 4 shows data obtained by A / D conversion of the signal output from the photomultiplier tube 15 when measured by the O 2 concentration measuring device 10. However, the xenon lamp 11 is 10 per second.
The light is turned on once, and the graph of FIG. 4 is a graph in which the average value of the output of the photomultiplier tube 15 every 3 seconds is plotted as one point. Since the sample gas does not contain SO 2 ,
All that appears in is noise. The result of calculating σ 2 / r (however, the number of data in r and σ 2 calculation section is 40) for this data is the graph of FIG. σ
The value of 2 / r hardly changed, and the value was 0.0
It is very small, around 1. Since the threshold value a is set to 1 in this embodiment, σ 2 / r <a is set over the entire area in the case of the data in FIG. Therefore, as described above, the value r calculated by the simple moving average method is used as the smoothed value s, and as shown in FIG. 6, a measurement value (solid line) curve in which noise is greatly reduced can be obtained. In FIG. 6, for reference, a curve in which a value calculated by the polynomial fitting method is used as a smoothed value is shown by a broken line, but the present invention shows that a sufficient noise reduction effect is obtained. Recognize.

【0012】当初はSO2を含まず、途中でSO2を蛍光
室(フローセル)13に導入した場合の測定値のカーブ
を図7に示す。この場合、ノイズよりも測定値の変化の
方が大きいため、図7に示す測定値カーブそれ自体で濃
度変化が十分わかりやすい形となっている。ところが、
これを単純移動平均法で平滑化すると、図9の破線で示
すように、濃度測定値カーブを大きく歪ませてしまう。
それに対し、本発明に係る方法に従ってσ2/rを算出
すると、図8に示すように、SO2を蛍光室(フローセ
ル)13に導入した直後からσ2/rの値が急激に増加
し、SO2濃度が大きく変化する間だけ、閾値aは1を
超える。従って、図3のステップS6、S8、S9の処
理により、この区間では多項式適合法によりが行なわ
れ、これが平滑化値sとして出力されるため、図9に示
すように、SO2の実際の濃度変化を良く表わしたカー
ブが得られる。
FIG. 7 shows a curve of measured values when SO 2 is not initially contained and SO 2 is introduced into the fluorescent chamber (flow cell) 13 on the way. In this case, since the change in the measured value is larger than that in the noise, the measured value curve itself shown in FIG. However,
If this is smoothed by the simple moving average method, the concentration measurement value curve is greatly distorted as shown by the broken line in FIG.
On the other hand, when σ 2 / r is calculated according to the method according to the present invention, as shown in FIG. 8, the value of σ 2 / r sharply increases immediately after SO 2 is introduced into the fluorescent chamber (flow cell) 13, The threshold value a exceeds 1 only while the SO 2 concentration changes greatly. Therefore, by the processing in step S6, S8, S9 of FIG. 3, the polynomial fitting method in this section is performed, since it is outputted as the smoothed value s, as shown in FIG. 9, the actual concentration of SO 2 A curve that shows the change well can be obtained.

【0013】なお、上記実施例では単純移動平均法と多
項式適合法とを用いたが、その他の平滑化法を用いるこ
とも可能である。また、使用する平滑化法は上記実施例
のように2種類のみに限られず、閾値を2種以上用意す
ることにより、3種以上の平滑化法を使い分けることも
できる。されに、これらの場合に、閾値の境界のところ
で平滑化法を截然と切り換えるのではなく、その両側の
所定区間内では両側の平滑化法に重み付けを加えて滑ら
かに移行させるようにしてもよい。
Although the simple moving average method and the polynomial fitting method are used in the above embodiment, other smoothing methods can be used. Further, the smoothing method to be used is not limited to two kinds as in the above embodiment, and three or more kinds of smoothing methods can be used properly by preparing two or more threshold values. In addition, in these cases, the smoothing method may not be abruptly switched at the boundary of the threshold value, but may be smoothed by weighting the smoothing method on both sides within a predetermined section on both sides thereof. .

【0014】[0014]

【発明の効果】本発明に係るノイズ除去方法では、σ2
/mの値を指標とし、この値が所定値よりも大きくなっ
たときは、測定対象量自身に変化が生じていることであ
ると考えられるため、ノイズ除去法がその変化を隠すこ
とがないように、ノイズ低減効果の緩やかな第1のノイ
ズ除去法を使用する。一方、σ2/mの値が所定値以下
であるときは、測定対象量自身の変化が無いか或いは緩
やかであると考えられるため、ノイズ低減効果の大きい
第2のノイズ除去法を使用する。これにより、真の測定
対象量をより良く表わす測定値を得ることができるよう
になる。本発明に係る方法ではこのように、採取された
測定値自身の変化の状況に応じてノイズ除去法を使い分
けるため、全体として、真の測定対象量の変化を見逃す
ことなく、しかも、ノイズを十分に抑制した測定値を得
ることができる。
According to the noise removal method of the present invention, σ 2
The value of / m is used as an index, and when this value becomes larger than a predetermined value, it is considered that there is a change in the measurement target amount itself, so the noise removal method does not hide the change. As described above, the first noise removal method having a gentle noise reduction effect is used. On the other hand, when the value of σ 2 / m is less than or equal to the predetermined value, it is considered that there is no change or a gradual change in the measurement target amount itself, so the second noise removal method having a large noise reduction effect is used. This makes it possible to obtain a measured value that better represents the true amount to be measured. As described above, in the method according to the present invention, the noise removal method is selectively used according to the situation of the change of the collected measurement value itself, so that the change of the true measurement target amount is not overlooked and the noise is sufficiently reduced. It is possible to obtain measured values that are suppressed.

【0015】更に、本発明に係るノイズ除去法の適用対
象となる測定データとしては、蛍光分析などの分析デー
タのみに限定されるものではなく、例えば材料試験、特
に疲労試験の測定データのように、データのばらつきが
大きく発生する測定データにも適用することができる。
Furthermore, the measurement data to which the noise removal method according to the present invention is applied is not limited to analysis data such as fluorescence analysis, but may be, for example, measurement data of material tests, especially fatigue tests. Also, the present invention can be applied to measurement data in which large variations in data occur.

【図面の簡単な説明】[Brief description of drawings]

【図1】 本発明の一実施例であるSO2濃度測定装置
の概略構成図。
FIG. 1 is a schematic configuration diagram of an SO 2 concentration measuring device that is an embodiment of the present invention.

【図2】 実施例のSO2濃度測定装置のデータ処理部
の構成を示すブロック図。
FIG. 2 is a block diagram showing the configuration of a data processing unit of the SO 2 concentration measuring device according to the embodiment.

【図3】 実施例のSO2濃度測定装置における測定値
の平滑化処理の手順を示すフローチャート。
FIG. 3 is a flowchart showing a procedure for smoothing a measured value in the SO 2 concentration measuring device according to the embodiment.

【図4】 SO2を含まない試料ガスのSO2濃度測定値
の変化を示すグラフ。
Figure 4 is a graph showing changes in SO 2 concentration measurement of the sample gas containing no SO 2.

【図5】 図4の測定値のσ2/rの変化を示すグラ
フ。
FIG. 5 is a graph showing changes in σ 2 / r of the measured values in FIG.

【図6】 図4の測定値に対して多項式適合法により平
滑化処理した場合のグラフ(破線)と、本発明の方法に
従って平滑化処理した場合のグラフ(実線)。
6A and 6B are graphs (broken line) when the measured values of FIG. 4 are smoothed by a polynomial fitting method and graphs (solid line) when smoothed according to the method of the present invention.

【図7】 途中でSO2ガスを注入した場合のSO2濃度
測定値の変化を示すグラフ。
FIG. 7 is a graph showing changes in SO 2 concentration measured values when SO 2 gas is injected midway.

【図8】 図7の測定値のσ2/rの変化を示すグラ
フ。
FIG. 8 is a graph showing changes in σ 2 / r of the measured values shown in FIG. 7.

【図9】 図7の測定値に対して単純移動平均法により
平滑化処理した場合のグラフ(破線)と、本発明の方法
に従って平滑化処理した場合のグラフ(実線)。
9A and 9B are a graph (broken line) when the measured values of FIG. 7 are smoothed by a simple moving average method and a graph (solid line) when smoothed according to the method of the present invention.

【符号の説明】[Explanation of symbols]

10…SO2濃度測定装置 11…キセノンランプ 12…光学フィルタ 13…蛍光室(フロー
セル) 14…光学フィルタ 15…光電子増倍管 16…データ処理部 20…出力装置 21…A/D変換器 22…CPU 23…インタフェイス 24…ROM 25…RAM
10 ... SO 2 concentration measuring device 11 ... Xenon lamp 12 ... Optical filter 13 ... Fluorescent chamber (flow cell) 14 ... Optical filter 15 ... Photomultiplier tube 16 ... Data processing unit 20 ... Output device 21 ... A / D converter 22 ... CPU 23 ... Interface 24 ... ROM 25 ... RAM

───────────────────────────────────────────────────── フロントページの続き (51)Int.Cl.6 識別記号 庁内整理番号 FI 技術表示箇所 H03H 21/00 8842−5J ─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. 6 Identification code Office reference number FI technical display location H03H 21/00 8842-5J

Claims (1)

【特許請求の範囲】[Claims] 【請求項1】 所定区間内に採取された測定値の分散を
該区間内の測定値の平均値で除した値が所定の閾値を超
えるときは第1のノイズ除去法を使用し、所定の閾値以
下のときは第1のノイズ除去法よりもノイズ低減効果の
大きい第2のノイズ除去法を使用することを特徴とする
測定値のノイズ除去方法。
1. When a value obtained by dividing the variance of the measurement values sampled in a predetermined section by the average value of the measurement values in the section exceeds a predetermined threshold value, the first noise removal method is used, and a predetermined noise removal method is used. A method of removing noise of a measured value, wherein a second noise removing method having a noise reducing effect larger than that of the first noise removing method is used when the value is equal to or less than a threshold value.
JP6114325A 1994-04-28 1994-04-28 Method for removing noise from measurement Pending JPH07294282A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP6114325A JPH07294282A (en) 1994-04-28 1994-04-28 Method for removing noise from measurement

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP6114325A JPH07294282A (en) 1994-04-28 1994-04-28 Method for removing noise from measurement

Publications (1)

Publication Number Publication Date
JPH07294282A true JPH07294282A (en) 1995-11-10

Family

ID=14635010

Family Applications (1)

Application Number Title Priority Date Filing Date
JP6114325A Pending JPH07294282A (en) 1994-04-28 1994-04-28 Method for removing noise from measurement

Country Status (1)

Country Link
JP (1) JPH07294282A (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006242750A (en) * 2005-03-03 2006-09-14 Riken Keiki Co Ltd Gas detection device
JP2009168812A (en) * 2008-01-14 2009-07-30 Avl List Gmbh Method and device for analyzing and evaluating measured data by means of measuring system
JP2013238479A (en) * 2012-05-15 2013-11-28 Seiko Epson Corp Detection apparatus
JP2014178242A (en) * 2013-03-15 2014-09-25 Shimadzu Corp Noise reduction device of time-series measurement signal
JP2015102339A (en) * 2013-11-21 2015-06-04 Dmg森精機株式会社 Surface shape measuring apparatus, and machine tool
JP2018091675A (en) * 2016-12-01 2018-06-14 株式会社島津製作所 Method for estimating absorbance of sample with approximate expression and spectroscopic analyzer

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006242750A (en) * 2005-03-03 2006-09-14 Riken Keiki Co Ltd Gas detection device
JP2009168812A (en) * 2008-01-14 2009-07-30 Avl List Gmbh Method and device for analyzing and evaluating measured data by means of measuring system
JP2013238479A (en) * 2012-05-15 2013-11-28 Seiko Epson Corp Detection apparatus
JP2014178242A (en) * 2013-03-15 2014-09-25 Shimadzu Corp Noise reduction device of time-series measurement signal
JP2015102339A (en) * 2013-11-21 2015-06-04 Dmg森精機株式会社 Surface shape measuring apparatus, and machine tool
JP2018091675A (en) * 2016-12-01 2018-06-14 株式会社島津製作所 Method for estimating absorbance of sample with approximate expression and spectroscopic analyzer

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