Data adjustment device

Abstract

To make a margin to a threshold more appropriate.SOLUTION: A data adjustment device for data sampled in a predetermined sampling period specifies, as minimum value determination data, minimum data among data sampled in a determination time that is a predetermined integral multiple of the predetermined sampling period for each predetermined sampling period, compares minimum value maximum data stored in a predetermined storage area with the minimum value determination data, and stores the minimum value determination data in the predetermined storage area as the minimum value maximum data when the minimum value determination data is larger than the minimum value maximum data.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a data conditioning device, and more particularly to a data conditioning device for data sampled at a predetermined sampling period. [Background technology]

[0002] A conventional technique of this type has been proposed for an induction motor driven by an inverter using a PWM inverter system with a carrier frequency and a modulation signal frequency, in which a vibration acceleration waveform collected by the induction motor is obtained in a form in which noise components have been removed (see, for example, Patent Document 1). This technique removes noise components occurring in the vibration spectrum, and then performs an inverse Fourier transform on the spectrum from which the noise components have been removed to obtain a vibration acceleration waveform collected by the induction motor in a form in which the noise components have been removed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-116251 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the above-mentioned technology, it is not possible to remove specific noise components unless the source of the noise is identified. Furthermore, even if a Fourier transform is performed and noise components are removed using a low-pass filter before making a judgment, if the noise value is large, noise components that cannot be removed by the filter will remain. By replacing abnormal data whose judgment time exceeds the threshold with a normal value, all values ​​become normal, but normal values ​​that are slightly below the threshold remain, resulting in an unnecessarily small margin for the threshold.

[0005] The data adjustment device of the present disclosure has a main object to make the margin for the threshold more appropriate. [Means for solving the problem]

[0006] The data adjustment device of the present disclosure employs the following means to achieve the above-mentioned main object.

[0007] The data adjustment device of the present disclosure includes: A data adjustment device for data sampled at a predetermined sampling period, comprising: identifying, as minimum value judgment data, the smallest data among the data sampled for a judgment time that is a predetermined integral multiple of the predetermined sampling period for each predetermined sampling period; comparing the minimum value maximum data stored in a predetermined storage area with the minimum value determination data, and if the minimum value determination data is greater than the minimum value maximum data, storing the minimum value determination data in the predetermined storage area as the minimum value maximum data; It is characterized by:

[0008] The data adjustment device disclosed herein identifies the minimum data among the data sampled at a judgment time that is a predetermined integral multiple of the predetermined sampling period as minimum value judgment data. Then, the device compares the minimum value judgment data with the minimum value maximum data stored in a predetermined storage area. If the minimum value judgment data is greater than the minimum value maximum data, the device stores the minimum value judgment data in the predetermined storage area as minimum value maximum data. That is, the device stores the maximum of the minimum value judgment data among the data sampled within the judgment time that starts at each predetermined sampling period as minimum value maximum data in the predetermined storage area. Consider a case where, if any of the data sampled within the judgment time falls below a threshold, data exceeding the threshold is removed as noise. If the difference between the minimum value maximum data stored in the predetermined storage area and the threshold is used as the margin, the margin relative to the threshold can be more appropriate than if the difference between the data immediately below the threshold and the threshold is used as the margin. This results in more appropriate noise removal. The predetermined sampling period, the judgment time, and the threshold can be appropriately determined based on the behavior of the data to be removed and the noise components.

[0009] The data adjustment device of the present disclosure may replace the minimum value with a maximum value and the maximum value with a minimum value. Specifically, the data adjustment device of the present disclosure may be a data adjustment device for data sampled at a predetermined sampling period, and may identify the maximum data among the data sampled at a judgment time that is a predetermined integral multiple of the predetermined sampling period as maximum value judgment data, compare the maximum value / minimum data stored in a predetermined storage area with the maximum value / minimum data, and, if the maximum value judgment data is smaller than the maximum value / minimum data, store the maximum value judgment data in the predetermined storage area as the maximum value / minimum data. Specifically, the minimum maximum value judgment data among the data sampled within a judgment time that starts at each predetermined sampling period is stored in the predetermined storage area as the maximum value / minimum data. In this case, considering a case in which, if any of the data sampled within the judgment time exceeds a threshold, data below the threshold is removed as noise, if the difference between the maximum value / minimum data stored in the predetermined storage area and the threshold is used as the margin, the margin relative to the threshold can be more appropriate than if the difference between the data immediately above the threshold and the threshold is used as the margin. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a configuration diagram showing an outline of the configuration of a data adjustment device 20 according to an embodiment of the present disclosure. [Figure 2] 10 is a flowchart showing an example of data processing executed by the data processing unit 24. [Figure 3] 10 is an explanatory diagram showing an example of the relationship between data SDn sampled at a sampling period and minimum and maximum data Dminmax. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0011] Next, a mode (embodiment) for carrying out the present disclosure will be described. FIG. 1 is a configuration diagram showing an outline of the configuration of a data adjustment device 20 according to an embodiment of the present disclosure. As shown in the figure, the data adjustment device 20 of the embodiment includes a data input unit 22 that inputs data from an external sensor 10 or the like, a data processing unit 24 that processes the input data, and a storage area 26 that stores minimum and maximum data Dminmax. The data processing unit 24 is a functional block realized by application software and a hardware configuration that performs data processing, as exemplified in FIG. 2. FIG. 2 is a flowchart showing an example of data processing executed by the data processing unit 24. The data processing is executed every time sampling data is input, i.e., at each sampling period.

[0012] When data processing is executed, first, the three most recent consecutive sampling data S(n), S(n-1), and S(n-2) are input as data D1, D2, and D3 (step S100). Next, the data with the smallest value among the data D1, D2, and D3 is set as minimum value determination data Dmin (step S110).

[0013] Next, it is determined whether the minimum value maximum data Dminmax is stored in the storage area 26 that stores the minimum value maximum data Dminmax (step S120).If it is determined that the minimum value maximum data Dminmax is not stored in the storage area 26, the minimum value determination data Dmin set in step S110 is stored in the storage area 26 as the minimum value maximum data Dminmax (step S140), and this processing is terminated.

[0014] If it is determined in step S120 that the minimum value maximum data Dminmax is stored in storage area 26, it is determined whether or not the minimum value judgment data Dmin set in step S110 is greater than the minimum value maximum data Dminmax stored in storage area 26 (step S1130). If it is determined that the minimum value judgment data Dmin is greater than the minimum value maximum data Dminmax, the minimum value judgment data Dmin is stored in storage area 26 as the minimum value maximum data Dminmax (step S140), and the process ends. That is, if it is determined that the minimum value judgment data Dmin is greater than the minimum value maximum data Dminmax, the minimum value maximum data Dminmax is replaced with the minimum value judgment data Dmin. On the other hand, if it is determined that the minimum value judgment data Dmin is equal to or less than the minimum value maximum data Dminmax, the process ends without replacing the minimum value maximum data Dminmax with the minimum value judgment data Dmin.

[0015] FIG. 3 is an explanatory diagram showing an example of the relationship between data SDn sampled at a sampling period and minimum / maximum data Dminmax. In the diagram, black dots SD1 to SD26 represent sampled data sampled in sampling order. Sampling begins at time T1, and when the data processing of FIG. 2 is executed immediately after sampled data SD3 is sampled at time T3, sampled data SD1 to SD3 are input as data D1 to D3, sampled data SD1 is set as minimum value determination data Dmin, and this minimum value determination data Dmin (sampled data SD1) is stored in storage area 26 as minimum / maximum data Dminmax. The square mark for sampled data SD1 in FIG. 3 indicates that it has been stored in storage area 26 as minimum / maximum data Dminmax.

[0016] Next, when sampling data SD4 is sampled at time T4, data processing is executed immediately thereafter, and sampling data SD2 to SD4 are input as data D1 to D3, and sampling data SD2 is set as minimum value determination data Dmin. Since this minimum value determination data Dmin (sampling data SD2) is larger than the minimum value maximum data Dminmax (sampling data SD1) stored in storage area 26 at that time, minimum value determination data Dmin (sampling data SD2) is stored in storage area 26 as minimum value maximum data Dminmax.

[0017] When the sampling data SD5 is sampled at time T5, data processing is executed immediately thereafter, and the sampling data SD3 to SD5 are input as data D1 to D3, and the sampling data SD5 is set as the minimum value determination data Dmin. Since this minimum value determination data Dmin (sampling data SD5) is smaller than the minimum value maximum data Dminmax (sampling data SD2) stored in storage area 26 at that time, the minimum value determination data Dmin (sampling data SD5) does not replace the minimum value maximum data Dminmax. From time T6 to time T24, the minimum value determination data Dmin does not replace the minimum value maximum data Dminmax, as at time T5.

[0018] When the sampling data SD25 is sampled at time T25, data processing is executed immediately thereafter, and the sampling data SD23 to SD25 are input as data D1 to D3, and the sampling data SD25 is set as the minimum value determination data Dmin. Since this minimum value determination data Dmin (sampling data SD25) is greater than the minimum value maximum data Dminmax (sampling data SD2) stored in the storage area 26 at that time, the minimum value determination data Dmin (sampling data SD25) is stored in the storage area 26 as the minimum value maximum data Dminmax.

[0019] Therefore, in the example of FIG. 3, the maximum value of the minimum values ​​(minimum-maximum data Dminmax) of three consecutive sampling data SD(n-2) to SD(n) between time T1 and time T26 is the value of sampling data SD25. Consider a case where an abnormality is determined to have occurred when three consecutive sampling data SD(n-2) to SD(n) exceed the threshold Dref using the threshold Dref in FIG. 3. In the example of FIG. 3, the three consecutive sampling data SD(n-2) to SD(n) do not exceed the threshold Dref, so no abnormality is detected. In this case, the margin for the threshold Dref is the difference between the threshold Dref and the minimum-maximum data Dminmax (sampling data SD25). When compared with the difference between the threshold Dref and the maximum value (sampling data D6) that does not exceed the threshold Dref as the margin, it is clear that it is more appropriate to use the difference between the threshold Dref and the minimum-maximum data Dminmax as the margin.

[0020] In the data adjustment device 20 of the embodiment described above, each time sampling of the sampling data SD is performed, the three consecutive sampled data SD(n-2) to SD(n) most recently sampled are input as data D1, D2, and D3, and the minimum value among them is set as minimum value judgment data Dmin. Then, when minimum value maximum data Dminmax is not stored in storage area 26, minimum value judgment data Dmin is stored in storage area 26 as minimum value maximum data Dminmax. When minimum value maximum data Dminmax is stored in storage area 26, if minimum value judgment data Dmin is greater than minimum value maximum data Dminmax, minimum value maximum data Dminmax is replaced with minimum value judgment data Dmin. As a result, if it is determined that an abnormality has occurred when all three consecutive sampled data SD(n-2) to SD(n) exceed threshold value Dref, the margin obtained from the difference between threshold value Dref and minimum value maximum data Dminmax can be more appropriate than the margin obtained from the difference between threshold value Dref and a maximum value that does not exceed threshold value Dref. As a result, more appropriate equipment design can be performed.

[0021] In the data adjustment device 20 of the embodiment, the minimum and maximum data Dminmax is obtained by performing data processing on the three most recently sampled consecutive sampled data SD(n-2) to SD(n) each time sampling of the sampling data SD is performed. However, the minimum and maximum data Dminmax may also be obtained by performing data processing on the two most recently sampled consecutive sampled data or four or more consecutive sampled data each time sampling of the sampling data SD is performed.

[0022] In the data adjustment device 20 of the embodiment, each time sampling of the sampling data SD is performed, the three consecutive sampled data SD(n-2) to SD(n) most recently sampled are input as data D1, D2, and D3, the smallest value among them is set as minimum value judgment data Dmin, and when the minimum value judgment data Dmin is larger than the minimum value maximum data Dminmax, the minimum value maximum data Dminmax is replaced with the minimum value judgment data Dmin. However, each time sampling of the sampling data SD is performed, the three consecutive sampled data SD(n-2) to SD(n) most recently sampled are input as data D1, D2, and D3, the largest value among them is set as maximum value judgment data Dmax, and when the maximum value judgment data Dmax is smaller than the maximum value minimum data Dmaxmin, the maximum value minimum data Dmaxmin is replaced with the maximum value judgment data Dmax. In this way, if it is determined that an abnormality has occurred when all three consecutive sampling data SD(n-2) to SD(n) are below the threshold value Dref, the margin obtained from the difference between the threshold value Dref and the maximum / minimum data Dmaxmin can be more appropriate than the margin obtained from the difference between the threshold value Dref and the minimum value that is not below the threshold value Dref. In this case, too, data processing may be performed on the most recently sampled two or four or more consecutive sampling data each time sampling data SD is performed to obtain the maximum / minimum data Dmaxmin.

[0023] The present disclosure has been described above using embodiments, but the present disclosure is not limited to these embodiments in any way, and it goes without saying that the present disclosure can be embodied in various forms within the scope that does not deviate from the gist of the present disclosure. [Industrial Applicability]

[0024] The present disclosure is applicable to the data conditioning device manufacturing industry. [Explanation of symbols]

[0025] 10 sensor, 20 data conditioning device, 22 data input section, 24 data processing section, 26 storage area.

Claims

[Claim 1] A data adjustment device for data sampled at a predetermined sampling period, comprising: identifying, as minimum value judgment data, the smallest data among the data sampled for a judgment time that is a predetermined integral multiple of the predetermined sampling period for each predetermined sampling period; comparing the minimum value maximum data stored in a predetermined storage area with the minimum value determination data, and if the minimum value determination data is greater than the minimum value maximum data, storing the minimum value determination data in the predetermined storage area as the minimum value maximum data; A data adjustment device comprising:

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