KR950007799B1 - Head contamination detecting method - Google Patents

Abstract

The method detects the start position of the contaminated VCR head by using ARMA(Auto Regressive Moving Average) algorithm and clears it at playback time. The method comprises the steps of: (a) detecting envelope from the reproduced image signal; (b) producing the digital signal by integrating the envelope signal; (c) sampling the digital signal; (d) computing the real value and expected value of the sampled data; (e) detecting the abrupt change of the expected value when the value exceeds the reference value. If the abrupt change of the expected value is detected, the head cleaning mechanism is activated.

Description

Head contamination detection method

1 is a graph showing a sudden decrease in output of a video signal to be reproduced.

2 is a diagram showing a configuration for a cleaning operation when head contamination occurs in accordance with the present invention.

3 is a flowchart for explaining the operation of the microcomputer shown in FIG.

4 and 5 are graphs illustrating prediction error detection of the autoregressive moving average method, respectively.

6 is a flowchart illustrating the operation of the automatic regression moving average method.

* Explanation of symbols for main parts of the drawings

10: microcomputer 11: tape

13: video head 15: drum

17: head cleaner 19: head cleaning actuator

The present invention relates to a method for predicting and removing contamination of a video head of a video cassette recorder (hereinafter referred to as a VCR).

In general, the head contamination problem of the VCR remains a problem that has not been solved until after the VCR, since the VCR must have a large relative speed contact between the tape and the rotating cylinder to record a high frequency video signal. This is a common problem for all magnetic recording mechanisms in which the recording medium and the recording head come into contact.

The causes of head contamination are first, the accumulation of tape magnetic material in the head due to prolonged use, and second, in the case of regenerating tape contaminated with sticky materials such as grease. There are many factors, such as when a magnetic body contaminates the head.

The head contamination measures that have been developed so far have been proposed such as cleaning tapes, built-in head cleaners, and video output level comparisons.

Since the cleaning tape method is made of synthetic resin or the like, there is a risk of overloading the deck mechanism due to the friction with the cylinder. In particular, in the case of the full loading method, the retraction may not be possible due to the large frictional force. In addition, the head and the running surface may be worn.

The built-in head cleaning method is to prevent the contamination of the head in advance by contacting the soft cleaner head built into the VCR. Regardless of the contamination of the head, there is a problem that the cassette is unconditionally operated even when the head is clean.

The video output comparison method is to operate the built-in head cleaner when the output falls below the reference value, taking advantage of the fact that the video output falls when the head is contaminated.

In detail, the video output of one field or one frame is analog / digital (A / D) converted, sampled, and the average value is compared with a preset value. At this time, if the average value is smaller than the reference value, it is determined that the output decreases due to head contamination.

However, if the foreign material adheres to the head and becomes contaminated, the signal characteristics of the inlet and the outlet of the video track are first degraded. This is a phenomenon that occurs due to the impact of the tape contacting the head and also due to the nature of the wound contact state between the head and the tape, the contact state on the inlet / outlet side has an unstable structure compared to other parts. A video signal waveform diagram relating to this phenomenon is shown in FIG. In FIG. 1, the dotted line indicates the sudden decrease in output occurring at the inlet / outlet side of the video track during the video signal of one field.

In the case of actual contamination such as the output signal waveform of FIG. 1, the video output comparison method, although the head contamination starts to occur, the average value is above the reference level, so that the contamination proceeds further until the signal output falls further. There was a problem of judging contamination. In addition, since the head contamination continues until the average value of the output decreases by the reference level, there is a problem that the screen is deteriorated, and even when the head cleaning is much hard.

Therefore, it is an object of the present invention to provide a method for initially detecting the starting point of head contamination using an automatic regression moving average method.

Another object of the present invention is to provide a method for removing head contamination during regeneration in accordance with detection of head contamination.

The method of the present invention for achieving the above object comprises the steps of: detecting an envelope signal of a video signal to be reproduced; Generating a digital signal by integrating the envelope signal; Sampling the digital signal; Calculating an actual value of the sampled data and a prediction value based on the actual value; Detecting a sudden change of the predicted value by more than a predetermined value according to the operation thereby detecting contamination of the head corresponding to the degradation of the video signal.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

Referring to Figures 2 and 3, there is shown a flow chart respectively illustrating the configuration and operation of predicting head contamination in accordance with the present invention and driving the head cleaning mechanism before further contamination progresses in accordance with this prediction.

The tape portion 11 wound on the head drum 15 is output by the head 13 as an image signal. This signal is detected as an envelope signal via a predetermined video signal processing circuit (not shown) (step A1) and input to the microcomputer 10. The microcomputer 10 integrates and samples the envelope signal (step A2).

The data of the sampled video signal may be represented by the following stochastic difference equation.

Where Y (K + 1) is the sampled video output at time K + 1,

W (K + 1) is discrete Gaussian white noise let,

ai is the model variable,

n is the number of system variables.

This equation is computed using the Auto Regressive Moving Average (ARMA) described in detail later (step A3). It is determined that the peak value of the error is generated as a result of the operation (step A5). As a result of the determination, if a peak of an error occurs, a warning is indicated by displaying the contamination on the display means 8 (step A6), and the head contamination is removed by operating the head cleaning actuator 9 (step A7). If no peak of the error has occurred, an automatic regression moving averaging operation is performed on the next sampled data.

The automatic regression moving average method uses prediction based on past values of the time-domain approach to detect degradation of video output occurring at the moment of head contamination as a sudden error in prediction error or system parameter. will be.

Referring to Figs. 4 and 5, graphs illustrating the prediction error detection of the automatic regression moving average method are respectively shown, where K represents the number of times to sample the data and calculate the operation loop. In addition, in the figure, the horizontal axis is time t, the vertical axis is video output Y, and reference numeral O is, for example, five sampled video outputs Y at time K + 1, and reference numeral Δ. Represents the predicted value Y of the video output. As a result, the prediction error ε (6) = Y (6) -Y (6) of the sixth sampled video output is obtained and the prediction error ε (7) = Y (7) -Y (7) of the seventh sampled video output. Will be

Next, the present invention to which the algorithm of the automatic regression moving average method is applied based on the above description will be described with reference to FIG. 6 shows a flowchart illustrating the steps for calculating the prediction error using the automatic regression moving average method.

In step B1, the number n of system variables is set. This is done by setting the number of variables on the horizontal axis (time axis) of Figs. 4 and 5 to predict the predicted value at the next time point (K + 1) using the average value of the video output at these points. It is a step for.

In step B2, the measurement vector ψ is initialized. This step measures the video outputs Y (1) to Y (n) for the number n of system variables so that ψ ^T (0) = [Y (1), Y (2),... Y (n)].

In step B3, the system variable θ is initialized. This step consists of θ (0) = [a ₁ , a ₂ ,... a _n ].

In step B4, prediction data Y (K + 1) is calculated. this is

It can be calculated as here (K) is a system variable calculated at time K.

In step B5, the actual measured data Y (K + 1) is measured.

In step B6, the prediction error ε (K + 1) is calculated. The prediction error can be described as the error between the actual measured data and the predicted data.

It can be represented as.

In step B7, in order to use the system variable θ as the system variable of the next prediction operation, the prediction error is zero, that is, ε (K + 1) Modify it to be zero.

this is It can be represented as

After this modification, the process proceeds to the step B4 again, and the above process is repeatedly performed. At this time, as described with reference to FIG. 3, when an abnormality of the system such as the head is contaminated with foreign matter occurs, the predictive error ε and the system variable θ change rapidly to approach the destroyed system. . This will also show the predictive error value at the peak level in the graph as shown in FIGS. 4 and 5. Therefore, by comparing the peak level with the preset level in the microcomputer 10, it is possible to more accurately determine the abnormality of the system, that is, the contamination state of the head. As a follow-up measure, the microcomputer 10 may display the head contamination on the display 8 and drive the head cleaning actuator 19 to remove the head contamination. In addition, even if contamination occurs during regeneration, decontamination can be performed in a state that a consumer cannot feel.

Claims (5)

Detecting an envelope of a video signal to be reproduced; Generating a digital signal by integrating the envelope signal; Sampling the digital signal; Calculating an actual value of the sampled data and a prediction value based on the actual value; Detecting contamination of the head corresponding to the degradation of the video signal by detecting a sudden change of the predicted value by more than a predetermined value according to the operation. The method of claim 1, wherein the digital signal generating comprises forming the video signal in the following manner. Where Y (K + 1) is the sampled video output at time K + 1, W (K + 1) is discrete Gaussian white noise let, ai is the model variable, n is the number of system variables. The method of claim 1, wherein the calculating step comprises: setting a number n of the system variable; The measurement vector is measured by Y (1) to Y (n) in order to initialize the system variable 1. Then, θ ^T (0) = [Y (1), Y (2),... Y (n)]; In order to initialize the system variable θ, 1 (0) = [a ₁ , a ₂ ,... a _n ]; In calculating the predictive data Y (K + 1), Y (K + 1) = θ ^T (K) · ψ (K) = a ₁ Y (1) + a ₂ Y (2) +... Calculating with + a _n Y (n); Measuring actual data Y (K + 1); Calculating a prediction error [epsilon] (K + 1), and calculating [epsilon] (K + 1) = Y (K + 1) -Y (K + 1); Applying ε (K + 1) = Y (K + 1) -θ ^T (K) · ψ (K) = 0 to correct the system variable θ to zero; Using the modified system variable as a system variable of a next prediction operation. 4. The method of claim 1, further comprising warning or displaying head contamination when a rapid change in the predicted value is detected. 2. The method of claim 1, further comprising driving a head cleaning mechanism (17 and 19) to remove head contamination when a rapid change in the predicted value is detected.