JPH05289737A - Signal processor - Google Patents

Abstract

PURPOSE:To attain the output of the continuous input signals even if these signals are suddenly changed by the noises by estimating the present value of the input signal from its past value when the difference between the present value and the precedent value of the input signal exceeds a certain level. CONSTITUTION:The angle signal phi given from a detector attached to a wheel 3 of a trolley 1 is converted into a position signal (x) by a signal converter 4 and inputted to a drive controller 5 through a signal processor 7. A difference arithmetic means 8 of the processor 7 fetches and stores the signals (x) in each fixed cycle and also reads out a signal xi of the present time and a signal xi-1 fetched in the precedent time to calculate the difference xeo between both signals. Then, a deciding means 9 decides whether the difference xeo is larger than the prescribed value xe or not. If xeo<xe is confirmed, the present value xi is read out and outputted by an output means 10. Meanwhile, the present value is estimated from the past signal value by an estimating means 11 and outputted if xeo>=xe is confirmed. Thus, the noises can be effectively suppressed.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a signal processing device,
In particular, the present invention relates to a signal processing device that is effective for noise suppression.

[0002]

2. Description of the Related Art Generally, in process control for controlling a machine based on a physical quantity, a sensor detects a physical quantity such as a position, temperature or flow rate, and a signal converter converts the physical quantity signal into a predetermined signal. Then, it is input to the control device, and thereby the drive control of the actuator such as the motor or the solenoid is performed.

[0003]

By the way, the physical quantity signal as described above is continuous with time and does not change so much per unit time. However, in reality, noise is likely to be inserted in such a signal, and the signal value may suddenly change suddenly, which may hinder control.

The present invention has been made in view of the above circumstances, and an object thereof is to provide a novel signal processing device capable of effectively taking measures against noise.

[0005]

In order to achieve the above object, the present invention stores and holds a continuously input signal at regular intervals and calculates the difference between the current value and the previous value of the signal. Difference calculation means, output means for outputting the current value as it is when the calculation result by this means is less than a predetermined value, and the current value from the past signal value when the calculation result by the difference calculation means is a predetermined value or more And a predicting means for predicting and outputting a value.

[0006]

According to the above construction, when the difference between the current value of the input signal and the previous value exceeds a certain value, the current value is predicted from the value of the past signal, so that the input signal is prevented by noise. Even if it changes abruptly, it can be output as a continuous signal.

[0007]

Embodiments of the present invention will be described below with reference to the accompanying drawings.

FIG. 1 shows an example of a control system to which the present invention is applied, here, a traveling control system of a trolley in a container crane. In the figure, reference numeral 1 denotes a trolley which hangs and traverses a container C, which is provided on a rail 2 via wheels 3 so as to be freely movable. A rotation angle detector (not shown) is attached to the wheel 3 of the trolley 1 to detect the traveling distance from the reference position, and the angle signal φ from this detector is detected by the signal converter 4. The signal x is converted into a signal x and input to the drive control device 5 via the signal processing device 7. The drive control device 5 drives and controls the traverse motor 6 of the trolley 1 according to a predetermined control program, whereby the trolley 1 is travel-controlled to a predetermined position.

The signal processing device 7 is for removing noise in the angle signal φ from the detector by digital processing, is mainly composed of a microcomputer, and has a difference calculating means 8 and a judging means 9, which are internal software, Output means 10
And a prediction means 11. As shown in FIG. 3, the difference calculating means 8 takes in the position signal x at every constant period τ and stores it as a database, and also reads out the signal x _{i at the} current time and the signal x _i−1 previously taken in and calculates the difference between them. Calculate x _e0 . This difference x _e0 is further determined by the determination means 9
It is determined whether or not it is equal to or _larger than a predetermined value x _e , and if the determination result is x _e0 <x _e , the output unit 10 reads and outputs the current value x _i . If the determination result by the determination means 9 is x _e0 ≧ x _e , the prediction means 1
According to 1, the current value is predicted and output from the signal values x _i-1 , x _i-2 , and x _{i-3 at the} past three points.

FIG. 2 shows a concrete example of the inference means 11. The inference means 11 has a knowledge base 12, a fuzzy inference unit 13 and a prediction formula operation unit 14,
The temporal characteristic of the position signal x is deduced based on the knowledge information stored in the knowledge base 12 in advance, and the prediction value x ₀ is obtained by performing the calculation processing of the prediction formula based on the obtained signal characteristic. That is, the following prediction formula is prepared in the prediction means 11 in advance.

X = x _i−1 + (2 + k) × b− (1−k) × a + x ₁ (1) where a and b are first-order difference values of the past three signals (a = x _{i -2} −x _i−3 , b = x _i−1 −x _i−2 ) k is a coefficient representing the signal characteristic x ₁ is the bias And, in accordance with this equation (1), the knowledge base 12 shows “current Knowledge information such as "what kind of value k in the formula (1) has when the difference x _e0 between the value x _i and the previous value x _i-1 is a value" is, for example, the rule R ₁ ~ Remembered by R ₃ .

R ₁ ; IF x _e0 = S THEN k = k _S R ₂ ; IF x _e0 = M THEN k = k _M R ₃ ; IF x _e0 = B THEN k = k _B where x _e0 is an input variable k is an output variable S, M and B are membership functions, k _S , k _M and k _B are membership function values. The fuzzy inference unit 13 receives a command from the determination means 9,
The approximate value of k is determined by the MIN-MAX method and the center of gravity method. Specifically, the difference x _e0 between the current value and the previous value is read from the memory, and the degree to which x _e0 belongs to the membership function S is calculated for rule R _{1 as} shown in FIG. Thereafter, similarly, the fitness is calculated for the other rules R ₂ and R ₃ as well, these fitnesses are combined, and the value of k is calculated from the position of the center of gravity of the combined result. When the value of k is obtained in this way, the values x _i-1 , x _i-2 , x _i-3 of the past three points and the bias value x ₁ are further read by the prediction formula operation unit 14,
These are substituted into the above equation (1) to calculate the predicted value x ₀ .

Next, the prediction formula used to predict the current value will be described.

As shown in FIG. 3, when an abnormality occurs in the position signal x _i at the current time t _i , the accurate value at that time is set to x.
_{When 0} is set, the first-order difference value, the second-order difference value, and the third-order difference value between the past three points are as follows.

A = x _i-2 −x _i-3 , b = x _i−1 −x _i-2 , c = x ₀ −x _i−1 (2) α = b−a, β = c− b (3) θ = β−α (4) Considering the case where the second-order difference value β is proportional to α between the times t _i-3 and t _i , θ = kα (5) Holds, and x ₀ is given by the above equations (2) to (5) as follows: x ₀ = x _i-1 + c = x _i-1 + (2 + k) × b− (1-k) × a (6) Further, further considering the bias, x ₀ = x _i−1 + (2 + k) × b− (1−k) × a + x ₁ and the above (1) is obtained.

Therefore, by using this equation (1), it is possible to obtain an accurate predicted value x ₀ in consideration of signal characteristics. However, since k in this equation (1) cannot be obtained in one place from the current value x _i , in this example, as described above, the difference x _e0 between the current value x _i and the previous value x _i-1. In contrast, the value of k is inferred by using a fuzzy expression such as “small”, “medium”, “large”, and the approximate value of k is determined.

As described above, in the signal processing device 7 of this embodiment, when the difference x _e0 between the current value x _i and the previous value x _i-1 of the position signal x input from the signal converter 4 is a predetermined value x _e or more. Since the present value is predicted from the past value, even if noise is included in the position signal x, it can be output to the drive control device 5 as a continuous signal, and the traveling control of the trolley 1 can be performed.

In addition, since the current value is predicted by inferring the characteristic of the position signal x and calculating the prediction equation (1) based on this signal characteristic, the predicted value in consideration of the signal characteristic is obtained. You can In addition, since the number of rules used for inference can be small, inference time can be shortened and real-time control can be performed.

In the present invention, θ = kα (equation
(5)), the prediction formula (Formula (1)) was calculated.
Other relational expressions such as α ² , θ = k / α may be used, and the membership function may be variously changed. The point is that a relational expression between θ and k should be created according to the characteristics of the position signal x, and the relation between k and x _e0 should be regularized. Alternatively, a plurality of packages including the above relational expressions, prediction expressions, and rules may be prepared, and a package may be appropriately selected and inferred according to an input signal.

[0020]

In summary, according to the present invention, even when noise is inserted in a continuously input signal, a signal when there is no noise can be predicted and output, so that a continuous signal is always obtained. The noise can be effectively prevented.

[Brief description of drawings]

FIG. 1 is a schematic block diagram showing an example of a system to which a signal processing device of the present invention is applied.

FIG. 2 is a diagram illustrating a configuration example of a prediction unit in the signal processing device.

FIG. 3 is a diagram showing an example of a change with time of a position signal.

FIG. 4 is a diagram showing an inference process in a prediction means.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 trolley 2 rail 7 signal processing device 8 difference calculation means 9 determination means 10 output means 11 prediction means 12 knowledge base 13 fuzzy inference unit 14 prediction formula calculation unit

Claims (1)

[Claims] 1. A difference calculation means for storing and holding continuously input signals at regular intervals and calculating a difference between a current value and a previous value of the signal, and a calculation result by this means being less than a predetermined value. In some cases, it is provided with an output means for outputting the current value as it is, and a prediction means for predicting and outputting the current value from the value of the past signal when the calculation result by the difference calculating means is a predetermined value or more. A signal processing device characterized by: