Measuring device, measuring method, and measuring program
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- ONO SOKKI CO LTD
- Filing Date
- 2024-11-13
- Publication Date
- 2026-05-25
AI Technical Summary
Existing measuring devices set thresholds and hysteresis values for pulse signals based on operator judgment, which is subjective and environment-dependent, leading to inconsistent and potentially noisy measurements of rotating or moving bodies.
A measuring device that calculates movement based on input signal amplitude, using an acquisition unit, classification unit, and threshold setting units to automatically set thresholds based on mean and variance of classified amplitude groups, applying a clustering model to classify and set appropriate first and second thresholds.
The device sets thresholds appropriately, reducing noise interference and enabling accurate measurement of rotating body angles, such as the engine's crankshaft, by classifying input signals into groups and setting thresholds based on statistical properties.
Smart Images
Figure 2026085591000001_ABST
Abstract
Description
[Technical Field]
[0001] This invention relates to a measuring device, a measuring method, and a measuring program. [Background technology]
[0002] The measuring device described in Patent Document 1 calculates engine rotational speed from a pulse signal representing the crank angle. In such measurements, engine rotational speed is measured using a threshold and hysteresis value set for the pulse signal. [Prior art documents] [Patent Documents]
[0003] [Patent Document 1] Japanese Patent Publication No. 2017-138100 [Overview of the project] [Problems that the invention aims to solve]
[0004] Incidentally, in the measuring device described in Patent Document 1 above, the amplitude and noise conditions of the pulse signal depend on the measurement environment, so the operator sets the threshold and hysteresis values themselves. For this reason, the setting of the threshold and hysteresis values is left to the operator's judgment. It should be noted that the same problem exists not only in the measurement of rotating bodies but also in the measurement of moving bodies that move in a straight line. [Means for solving the problem]
[0005] A measuring device for solving the above problems is a measuring device that calculates the amount of movement of a measurement target based on the on and off states of an input signal having an amplitude, and comprises: an acquisition unit that, in the case of rising edge detection, detects the input signal on when the amplitude value of the input signal exceeds a first threshold, and detects the input signal off when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold; in the case of falling edge detection, detects the input signal on when the amplitude value of the input signal falls below a second threshold, and detects the input signal off when the amplitude value of the input signal exceeds a first threshold, and acquires the input signal for a predetermined period as a threshold setting signal; a classification unit that classifies the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating on and a second group consisting of amplitude values indicating off; a first threshold setting unit that sets the first threshold based on the first mean value and first variance value of the amplitude values of the first group; and a second threshold setting unit that sets the second threshold based on the second mean value and second variance value of the amplitude values of the second group.
[0006] According to the above configuration, the threshold setting signals, which are input signals for a predetermined period, are classified into a first group and a second group. A first threshold is set based on the first mean and first variance of the amplitude values of the first group, and a second threshold is set based on the second mean and second variance of the amplitude values of the second group. Therefore, the first and second thresholds, which were previously set based on the user's judgment, can now be appropriately set according to the input signal being measured.
[0007] With respect to the above-mentioned measuring device, it is preferable that the classification unit applies a clustering model to the amplitude values constituting the threshold setting signal for classification. With the above configuration, the mean and variance can be classified by applying a clustering model.
[0008] With respect to the above measuring device, it is preferable that the classification unit extracts extreme values and classifies the extracted extreme values when the input signal is a continuously fluctuating waveform. With the above configuration, since continuous fluctuating waveforms cannot be classified directly, the first and second thresholds can be set by classifying the extracted extreme values.
[0009] With respect to the above measuring device, it is preferable that the object to be measured is a rotating body, and the input signal is an input signal detected in conjunction with the rotation of the rotating body. According to the above configuration, the rotation angle and rotation speed of the rotating body can be measured.
[0010] A measurement method for solving the above problems is a measurement method for calculating the amount of movement of a measurement object based on the on and off states of an input signal having amplitude, comprising: an acquisition step of acquiring the input signal as a threshold setting signal for a predetermined period, in the case of rising edge detection, when the amplitude value of the input signal exceeds a first threshold, the input signal is detected as on, and when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold, the input signal is detected as off; in the case of falling edge detection, when the amplitude value of the input signal falls below a second threshold, the input signal is detected as on, and when the amplitude value of the input signal exceeds a first threshold, the input signal is detected as off; a classification step of classifying the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating on and a second group consisting of amplitude values indicating off; a first threshold setting step of setting the first threshold based on the first mean value and first variance value of the amplitude values of the first group; and a second threshold setting step of setting the second threshold based on the second mean value and second variance value of the amplitude values of the second group.
[0011] According to the above method, the threshold setting signals, which are input signals for a predetermined period, are classified into a first group and a second group. A first threshold is set based on the first mean and first variance of the amplitude values of the first group, and a second threshold is set based on the second mean and second variance of the amplitude values of the second group. Therefore, the first and second thresholds, which were previously set based on the user's judgment, can now be appropriately set according to the input signal being measured.
[0012] A measurement program that solves the above problems is a measurement program that calculates the amount of movement of a measurement object based on the on and off states of an input signal having an amplitude, and in the case of rising edge detection, it detects the input signal being on when the amplitude value of the input signal exceeds a first threshold, and detects the input signal being off when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold, and in the case of falling edge detection, it detects the input signal being on when the amplitude value of the input signal falls below a second threshold, and detects the input signal being off when the amplitude value of the input signal exceeds a first threshold, and causes a computer to execute an acquisition step of acquiring the input signal for a predetermined period as a threshold setting signal, a classification step of classifying the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating on and a second group consisting of amplitude values indicating off, a first threshold setting step of setting the first threshold based on the first mean value and first variance value of the amplitude values of the first group, and a second threshold setting step of setting the second threshold based on the second mean value and second variance value of the amplitude values of the second group.
[0013] According to the above program, the threshold setting signals, which are input signals for a predetermined period, are classified into a first group and a second group. A first threshold is set based on the first mean and first variance of the amplitude values of the first group, and a second threshold is set based on the second mean and second variance of the amplitude values of the second group. Therefore, the first and second thresholds, which were previously set based on the user's judgment, can now be appropriately set according to the input signal being measured. [Effects of the Invention]
[0014] According to the present invention, the threshold can be set appropriately. [Brief explanation of the drawing]
[0015] [Figure 1] This block diagram shows the schematic configuration of a measuring device according to one embodiment. [Figure 2] This graph illustrates the detection of on / off status of an input signal by the measuring device of the same embodiment. [Figure 3]A graph for explaining the detection of the on / off of an input signal by the measuring device of the same embodiment. [Figure 4] A flowchart showing a process for setting a threshold value for detecting the on / off of an input signal by the measuring device of the same embodiment. [Figure 5] A graph showing an input signal measured by the measuring device of the same embodiment. [Figure 6] A graph showing the frequency of each amplitude of an input signal measured by the measuring device of the same embodiment. [Figure 7] A graph showing the likelihood of each amplitude of an input signal measured by the measuring device of the same embodiment. [Figure 8] A graph showing a threshold value for detecting the on / off of an input signal by the measuring device of the same embodiment.
Mode for Carrying Out the Invention
[0016] (This Embodiment) Hereinafter, an embodiment of a measuring device, a measuring method, and a measuring program will be described with reference to FIGS. 1 to 8. The measurement target of the measuring device is the angle of the crankshaft of the engine.
[0017] (Measuring Device 10) As shown in Figure 1, the measuring device 10 may be configured as one or more processors that execute various processes according to a computer program (software). The processes executed by the measuring device 10, i.e., the processor, include a measurement method. The measurement method includes an acquisition step, a classification step, a first threshold setting step, and a second threshold setting step, which will be described later. The measuring device 10 may also be configured as a circuit including one or more dedicated hardware circuits, such as application-specific integrated circuits (ASICs), or a combination thereof, that execute at least some of the various processes. The processor includes a CPU and memory such as RAM and ROM. The memory stores program code or instructions configured to cause the CPU to execute the processes. The memory, i.e., computer-readable media, includes any available media that can be accessed by a general-purpose or dedicated computer. The programs stored in the computer-readable media include a measurement program. The measurement program causes the computer to execute the acquisition step, the classification step, the first threshold setting step, and the second threshold setting step.
[0018] As shown in Figure 2 or Figure 3, the measuring device 10 calculates the angle of the engine's crankshaft 20 based on the on and off states of an input signal having amplitude. The input signal is input as a voltage and converted into an angle by software calculation. The measuring device 10 detects the on and off states of the input signal by rising edge detection or falling edge detection. In the case of rising edge detection, the measuring device 10 detects the input signal as on when the amplitude value of the input signal exceeds a first threshold, and detects the input signal as off when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold. In this embodiment, the on and off states of the input signal are detected by rising edge detection. On the other hand, in the case of falling edge detection, the measuring device 10 detects the input signal as on when the amplitude value of the input signal falls below a second threshold, and detects the input signal as off when the amplitude value of the input signal exceeds a first threshold.
[0019] Here, the on and off states of the input signal are detected by the first and second thresholds, so it is necessary to set the first and second thresholds. In the case of rising edge detection, the second threshold corresponds to the hysteresis value at which the input signal returns from on to off, and the difference between the first and second thresholds corresponds to the hysteresis. As shown in Figure 2, if the input signal contains noise, and the second threshold is close to the first threshold and the hysteresis is small, there is a risk that the on and off states will be detected by the noise. On the other hand, as shown in Figure 3, by adjusting the second threshold to avoid detecting noise, and moving the second threshold away from the first threshold to increase the hysteresis, it is possible to detect the on and off states of the input signal without noise. Thus, conventionally, the measurer set the first and second thresholds based on their own judgment. Therefore, in this embodiment, the measuring device 10 sets appropriate first and second thresholds on its own.
[0020] As shown in Figure 1, the measuring device 10 receives either a pulse signal as a crankshaft angle signal from an angle sensor 21 that detects the angle of the engine's crankshaft 20, or a tooth-drop pulse signal as a crankshaft angle signal from the engine ECU 30. The operator can select either the pulse signal or the tooth-drop pulse signal. The engine's crankshaft 20 corresponds to a rotating body. The measuring device 10 acquires the crankshaft angle signal detected as the engine's crankshaft 20 rotates. The pulse signal input from the angle sensor 21 is a square wave.
[0021] The measuring device 10 comprises an acquisition unit 11, a classification unit 12, a first threshold setting unit 13, a second threshold setting unit 14, and a measuring unit 15. The acquisition unit 11 acquires the crankshaft angle signal over a predetermined period as a threshold setting signal. That is, the acquisition unit 11 acquires the crankshaft angle signal over a predetermined period in order to set a threshold. The predetermined period is initially set to 4 [ms], and can be changed in multiple steps from 4 to 262 [ms] depending on conditions such as the rotational speed of the object to be measured and the number of pulses. This predetermined period can be changed manually by the person taking the measurement, or it can be set automatically by the measuring device 10. The predetermined period can be set arbitrarily. The acquired crankshaft angle signal is used as the threshold setting signal in order to set the threshold.
[0022] The classification unit 12 classifies the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating "on" and a second group consisting of amplitude values indicating "off". The classification unit 12 classifies the amplitude values constituting the threshold setting signal by applying a clustering model. In this embodiment, a Gaussian mixture model is adopted as the clustering model. In the Gaussian mixture model, the mean value (μ) when the maximum and minimum values of the threshold setting signal are considered to follow a normal distribution is used. + ,μ - ) and variance (σ + ,σ - ) and can be estimated respectively. The mean of the first group is the first mean (μ + ) and the variance of the first group is the first variance (σ + Let the mean of the second group be the second mean (μ). - ) and the variance of the second group is the second variance (σ - )
[0023] Furthermore, if the crankshaft angle signal is a continuously fluctuating waveform, it will contain many values other than the maximum and minimum values. For this reason, the classification unit 12 extracts the extreme values and then classifies the extracted extreme values. An example of a continuously fluctuating waveform is the tooth-missing pulse signal output from the engine ECU 30. The classification unit 12 determines whether each point in the waveform of the tooth-missing pulse signal is an extreme value and converts the tooth-missing pulse signal into data containing only the extreme values.
[0024] The first threshold setting unit 13 sets a first threshold based on the first average value and the first variance value of the first group of amplitude values composed of amplitude values indicating on. That is, the threshold TH, which is the first threshold used for detecting the crankshaft angle signal, is TH = μ + - n * σ + and is obtained as follows. Here, n is a real number, and an optimal value for measurement is set. For example, n is the minimum value such that the threshold TH is smaller than the minimum value of the first group. In the present embodiment, when the threshold setting signal is a pulse signal, n = 15, and when the threshold setting signal is a missing tooth pulse signal, n = 3.
[0025] The second threshold setting unit 14 sets a second threshold based on the second average value and the second variance value of the second group of amplitude values composed of amplitude values indicating off. That is, the hysteresis value HI, which is the second threshold used for detecting the crankshaft angle signal, is HI = μ - + n * σ - and is obtained as follows. Here, n is a real number, and an optimal value for measurement is set. For example, n is the maximum value such that the hysteresis value HI is larger than the maximum value of the second group. In the present embodiment, when the threshold setting signal is a pulse signal, n = 15, and when the threshold setting signal is a missing tooth pulse signal, n = 3.
[0026] The measurement unit 15 measures the angle of the crankshaft 20 of the engine by detecting the on and off of the crankshaft angle signal using the first threshold and the second threshold set as described above. The measuring device 10 outputs the measurement result to a display device (not shown) or the like.
[0027] (Operation of the present embodiment) Next, referring to FIGS. 4 to 8 together, the setting process of the threshold used for detecting the crankshaft angle signal of the measuring device 10 will be described.
[0028] First, the measuring device 10 acquires the crankshaft angle signal (step S1). That is, the acquisition unit 11 acquires the crankshaft angle signal over a predetermined period as a threshold setting signal. The crankshaft angle signal in Figure 5 is a pulse signal and contains noise near the maximum and minimum values. Step S1 corresponds to the acquisition step.
[0029] Next, the measuring device 10 determines whether the input signal, the crankshaft angle signal, is a pulse signal (step S2). That is, the classification unit 12 determines that the crankshaft angle signal is not a pulse signal if it is a continuously fluctuating waveform. The encoder signal output from the angle sensor 21 is a pulse signal, and the ECU signal output from the engine ECU 30 is a missing-tooth pulse signal. If the classification unit 12 determines that the input signal is a pulse signal (step S2: YES), it proceeds to step S4.
[0030] On the other hand, if the classification unit 12 determines that the input signal is not a pulse signal (step S2: NO), it extracts extreme values from the threshold setting signal (step S3). That is, the classification unit 12 determines whether each point in the continuous fluctuation waveform of, for example, a missing tooth pulse signal is an extreme value and converts the missing tooth pulse signal into data consisting only of extreme values. When the classification unit 12 extracts a maximum value, it determines that it is larger than several points before and after it, and when it extracts a minimum value, it determines that it is smaller than several points before and after it. The classification unit 12 then extracts the frequency of extreme values for each amplitude. Figure 6 is a graph shown to illustrate the frequency of occurrence of extreme values extracted in step S3. Therefore, it is not necessary to output a graph.
[0031] Next, the measuring device 10 applies a Gaussian mixture model (step S4). That is, the classification unit 12 applies a Gaussian mixture model to classify the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating ON and a second group consisting of amplitude values indicating OFF. The classification unit 12 applies a Gaussian mixture model to classify the first mean value (μ) which is the average value of the first group. + ) and the first variance (σ) which is the variance of the first group +) and the second mean value (μ) which is the mean value of the second group. - ) and the second variance (σ), which is the variance of the second group. - ) and can be estimated. Step S4 corresponds to the classification step.
[0032] Next, the measuring device 10 sets a first threshold and a second threshold (step S5). Specifically, the first threshold setting unit 13 sets the first threshold based on the first mean value and the first variance value of the amplitude values of the first group. The second threshold setting unit 14 sets the second threshold based on the second mean value and the second variance value of the amplitude values of the second group. As shown in Figure 7, the minimum likelihood value represents the amplitude that best separates the first group and the second group. If it is greater than the minimum likelihood value, it is the first group, and if it is less than the maximum likelihood value, it is the second group. The first mean value is the mean value in the larger cluster in Figure 7, and is approximately 3.2. The second mean value is the mean value in the smaller cluster in Figure 7, and is approximately 0.05. Furthermore, 15σ of the upper limit of the Gaussian distribution corresponds to the first threshold, and 15σ of the lower limit of the Gaussian distribution corresponds to the second threshold. Step S5 corresponds to the first threshold setting step and the second threshold setting step.
[0033] As shown in Figure 8, the 15σ of the upper limit Gaussian distribution, which is the first threshold set as described above, is lower than the noise contained around the maximum value of the crankshaft angle signal and is close to the maximum value. Also, the 15σ of the lower limit Gaussian distribution, which is the second threshold set as described above, is higher than the noise contained around the minimum value of the crankshaft angle signal and is close to the minimum value. Therefore, the measuring device 10 can detect the on / off state of the crankshaft angle signal using the optimal threshold and measure the rotation angle of the engine's crankshaft 20.
[0034] (Effects of this embodiment) Next, the effects of this embodiment will be described. (1) The threshold setting signals, which are crankshaft angle signals over a predetermined period, are classified into a first group and a second group. A first threshold is set based on the first mean and first variance of the amplitude values of the first group, and a second threshold is set based on the second mean and second variance of the amplitude values of the second group. As a result, the first and second thresholds, which were previously set based on the user's judgment of the measuring device 10, can now be appropriately set according to the actual crankshaft angle signals of the engine.
[0035] (2) By applying a Gaussian mixture model as the clustering model, the mean and variance can be classified. (3) Since the input signal cannot be classified directly if it is a continuously fluctuating waveform, the first and second thresholds can be set by classifying it based on the extracted extreme values.
[0036] (4) The measuring device 10 can measure the rotation angle of the crankshaft 20 of the engine, which is a rotating body, using a first threshold and a second threshold that it sets based on the on and off states of the crankshaft angle signal input from the angle sensor 21.
[0037] (Other embodiments) The above embodiment can be implemented with the following modifications. The above embodiment and the following modifications can be combined with each other to the extent that they do not contradict each other technically.
[0038] In the above embodiment, a Gaussian mixture model was applied as the clustering model. However, the clustering model is not limited to a Gaussian mixture model. Other clustering models such as K-means, group mean method, and Ward's method may be applied as long as it is possible to divide the data into two classes and obtain the mean and variance from the respective normal distributions.
[0039] In the above embodiment, when the input signal is a continuously fluctuating waveform, the classification unit 12 extracts the extreme values and then classifies the extracted extreme values. However, if it is known in advance that the input signal is not a continuously fluctuating waveform, clustering may be performed without determining whether the input signal is a pulse signal or not.
[0040] In the above embodiment, the measuring device 10 measured the rotation angle of the engine's crankshaft 20. However, the measuring device 10 is not limited to the engine's crankshaft 20; it may also measure the rotation angle of other rotating bodies by acquiring an input signal that detects the rotation of a rotating body. Furthermore, the measuring device 10 is not limited to rotating bodies; it may also measure the amount of movement of a moving body in linear motion. [Explanation of symbols]
[0041] 10… Measuring device 11…Acquisition part 12...Classification section 13...First threshold setting unit 14...Second threshold setting section 20... Crank axle 21…Angle sensor 30…Engine ECU
Claims
1. A measuring device that calculates the amount of movement of a target to be measured based on the on and off states of an input signal having amplitude, In the case of rising edge detection, when the amplitude value of the input signal exceeds a first threshold, the input signal is detected as being on, and when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold, the input signal is detected as being off. In the case of falling edge detection, if the amplitude value of the input signal falls below the second threshold, the input signal is detected as being on, and if the amplitude value of the input signal exceeds the first threshold, the input signal is detected as being off. An acquisition unit that acquires the input signal during a predetermined period as a threshold setting signal, A classification unit that classifies the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating "on" and a second group consisting of amplitude values indicating "off", A first threshold setting unit sets the first threshold based on the first mean value and first variance value of the amplitude values of the first group, The system includes a second threshold setting unit that sets the second threshold based on the second mean value and second variance value of the amplitude values of the second group. Measuring device.
2. The classification unit applies a clustering model to the amplitude values that constitute the threshold setting signal and classifies them. The measuring device according to claim 1.
3. The classification unit extracts extreme values and classifies the extracted extreme values if the input signal is a continuously fluctuating waveform. The measuring device according to claim 1 or 2.
4. The object to be measured is a rotating body, The input signal is a signal detected in conjunction with the rotation of the rotating body. The measuring device according to claim 1.
5. A measurement method for calculating the amount of movement of a measurement object based on the on and off states of an input signal having amplitude, In the case of rising edge detection, when the amplitude value of the input signal exceeds a first threshold, the input signal is detected as being on, and when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold, the input signal is detected as being off. In the case of falling edge detection, if the amplitude value of the input signal falls below the second threshold, the input signal is detected as being on, and if the amplitude value of the input signal exceeds the first threshold, the input signal is detected as being off. An acquisition step of acquiring the input signal during a predetermined period as a threshold setting signal, A classification step of classifying the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating "on" and a second group consisting of amplitude values indicating "off", A first threshold setting step of setting the first threshold based on the first mean value and first variance value of the amplitude values of the first group, The process includes a second threshold setting step of setting the second threshold based on the second mean value and second variance value of the amplitude values of the second group. Measurement method.
6. A measurement program that calculates the amount of movement of a target to be measured based on the on and off states of an input signal having amplitude, In the case of rising edge detection, when the amplitude value of the input signal exceeds a first threshold, the input signal is detected as being on, and when the amplitude value of the input signal falls below a second threshold which is smaller than the first threshold, the input signal is detected as being off. In the case of falling edge detection, if the amplitude value of the input signal falls below the second threshold, the input signal is detected as being on, and if the amplitude value of the input signal exceeds the first threshold, the input signal is detected as being off. An acquisition step of acquiring the input signal during a predetermined period as a threshold setting signal, A classification step of classifying the amplitude values constituting the threshold setting signal into a first group consisting of amplitude values indicating "on" and a second group consisting of amplitude values indicating "off", A first threshold setting step of setting the first threshold based on the first mean value and first variance value of the amplitude values of the first group, The computer is made to perform a second threshold setting step, which involves setting the second threshold based on the second mean value and second variance value of the amplitude values of the second group. Measurement program.