CN120045425B - Optimization processing method and device for electronic information - Google Patents

Abstract

A method and device for optimizing the processing of electronic information, belonging to the field of information processing technology, wherein when the variation trend of the electronic information in the current information segment is determined to be close to linear, a wavelet closed-value denoising method with better fault tolerance can be used to perform denoising treatment on the current information segment, thereby ensuring the accuracy of the determined denoised data; and by combining the interference value benchmark and variation speed of the current information segment, a denoising threshold is actively configured when the wavelet closed-value denoising method is performed on the current information segment, thereby improving the efficiency of the denoised electronic information while further improving the accuracy of the obtained denoised electronic information, that is, the processed electronic information.

Description

Method and device for optimizing processing of electronic information

Technical Field

The present invention belongs to the technical field of information processing, and in particular relates to a method and device for optimizing processing of electronic information.

Background Art

As mentioned in the prior art solution with patent publication number "CN220828710U", the current sampling and monitoring of electronic information often uses a display screen and a sampling device connected to a controller. The sampling device is set on the target to be measured. The sampling device is used to sample the electronic information of the target to be measured and transmit it to the controller. The controller is used to transmit the collected electronic information of the target to be measured to the display screen for display, thereby achieving the purpose of sampling and monitoring of electronic information.

In order to ensure the accuracy and authenticity of electronic information, before the collected electronic information of the measured target is transmitted to the display screen for display, it is often necessary to use a noise reduction algorithm to perform noise reduction on the electronic information to remove interference values. The noise reduction state is often constant, while the interference value properties of different application environments are often different. The same noise reduction state is often not suitable for all conditions, and directly removing the information will often result in the loss of useful information, reducing the accuracy of the processed electronic information. In addition, there are many noise reduction states to be set, and each noise reduction state is a corresponding parameter. The amount of calculation required for different environments is not low, and the efficiency is insufficient.

Summary of the Invention

In order to solve the defects in the existing technology, the present invention proposes an optimized processing method and device for electronic information. If the change trend of the electronic information in the current information segment is close to linear, the wavelet closed value denoising method with better fault tolerance can be used to perform denoising treatment on the current information segment, thereby ensuring the accuracy of the identified denoised data; and in combination with the interference value benchmark and change speed of the current information segment, the denoising threshold when performing the wavelet closed value denoising method on the current information segment is actively configured, which can improve the efficiency of the denoised electronic information while improving the accuracy of the obtained denoised electronic information, that is, the processed electronic information.

The present invention utilizes the following technical solutions.

A method for optimizing processing of electronic information, comprising:

The sampling device samples the electronic information of the measured object and transmits it to the controller, which processes the collected electronic information of the measured object and transmits the processed electronic information to the display screen for display;

The controller processes the electronic information of the detected target, including:

Step 1: Obtain electronic information of the target and arrange it into an electronic information queue in the order of sampling time points. Identify the latest change value from the current information in the electronic information queue, and treat the information segment formed by the current information and the change value as the current information segment.

Step 2: Calculate the interference value reference of the current information segment, use the interference value reference as a parameter for inputting the corresponding operation, and perform the corresponding operation to obtain the noise reduction threshold value of the current information segment;

Step 3: Perform a simulation on the current information segment to obtain a simulated line on a Cartesian coordinate system. The value obtained by dividing the value by the average distance between the electronic information in the current information segment and the simulated line is used as the simulated value of the simulated line. The value obtained by multiplying the tangent of the angle between the simulated line and the Cartesian coordinate system by the simulated value is used as the change speed of the current information segment.

Step 4, refresh the noise reduction threshold, use the refreshed noise reduction threshold as the threshold to apply the wavelet closed value noise reduction method to perform noise reduction on the current information segment, obtain the noise reduction information of the current information, and use the noise reduction information as the processed electronic information.

Furthermore, in step 1, the change value is an information point in the electronic information queue that is different from the change trend of several previous electronic information, and is used to cut the electronic information queue into several information segments with similar change trends.

Furthermore, in step 1, the method for determining the latest change value from the current information in the electronic information queue includes:

Perform change value detection on the electronic information queue to obtain all change values in the electronic information queue, and take the change value with the smallest time interval between its corresponding sampling time point and the current time point as the latest change value from the current information in the electronic information queue.

Furthermore, in step 1, after the latest change value from the current information in the electronic information queue is determined, the information segment between the change value and the current information is regarded as the current information segment.

Furthermore, in step 2, the predefined quantity is set to 12. After the interference value reference a of the current information segment is determined, the noise reduction threshold value L 0 of the current information segment is L ₀ =12 ^a .

Furthermore, in step 2, the method of calculating the interference value reference of the current information segment includes:

Step 2-1: Determine the optimal grouping size for grouping the current information segment. Use a natural number between 1 and the optimal grouping size as a standard size. Use each standard size as the grouping size for grouping the current information segment. Perform grouping on the current information segment several times to obtain grouping information for each grouping.

Step 2-2, calculate the average of the distances between the centroid and the nearest centroid after the random grouping is completed, and obtain the discrete amount of the grouping information of the random grouping;

In step 2-3, the discrete quantities of the grouped information of each group are subtracted pairwise to obtain a subtraction quantity queue, the total sum of the elements in the subtraction quantity queue is calculated, and the inverse value of the total sum is normalized to obtain the interference value benchmark of the current information segment.

Furthermore, in step 2-1, the optimal grouping amount is the optimal number of groups when performing grouping on the current information segment, and the optimal grouping amount is determined using a cross-validation method;

Use the expectation maximization algorithm to group the current information segments;

After determining the optimal grouping quantity l when grouping the current information segment, a natural number between one and l can be used as a standard quantity. Here, the standard quantity includes one and l, that is, the standard quantity is the queue {1,2...l}.

Furthermore, in step 2-2, the distance between any centroid after any grouping is achieved and the corresponding nearest centroid is the L2 norm.

Furthermore, in step 2-2, the distance between the centroid and the nearest centroid is the global distance, and the method for determining the global distance is:

Obtain the nearest group of any group after any grouping is completed, calculate the average of the distances between the information points in the nearest group and the centroid of the nearest group, and divide the value obtained by one by the average as the grouping optimal value of the nearest group; multiply the grouping optimal value by the distance between the centroid of any group and the centroid of the nearest group as the global distance between the centroid of any group and the centroid of the nearest group;

That is, the global distance between the centroid of the jth group obtained after the kth grouping is achieved and the centroid of the most adjacent group of the jth group obtained after the kth grouping is achieved Here, is the distance between the centroid of the jth group obtained after the kth grouping is completed and the centroid of the most adjacent group of the jth group obtained after the kth grouping is completed, It is the optimal number of groups of the closest groupings of the jth grouping obtained after the kth grouping is completed;

Then, after determining the centroid of any group after any grouping is completed and the global distance between the centroid of the group and the nearest centroid of the group, the discrete amount of the grouping information of the group can be calculated, that is, the following equation can be calculated:

In the equation, _Gk is the discrete amount of grouping information of the kth grouping; is the distance between the centroid of the jth group obtained after the kth grouping is completed and the centroid of the most adjacent group of the jth group obtained after the kth grouping is completed; is the optimal number of groups of the closest groupings of the jth grouping obtained after the kth grouping is achieved; _pk is the number of groups obtained after the kth grouping is achieved.

Furthermore, steps 2-3 specifically include:

Initially, a discrete quantity queue of group information obtained from the first grouping to the last grouping is defined as Y _G = {G ₁ , G ₂ , ...G ₁ }, where G ₁ , G ₂ , and G ₁ are discrete quantities of group information obtained when grouping the current information using a grouping size of one, a grouping size of two, and an optimal grouping size, respectively; then, a subtraction quantity queue ΔZ _G = {ΔG ₁ , ΔG ₂ , ...ΔG _1-1 } is calculated for the discrete quantity queue, where ΔG ₁ = |G ₂ -G ₁ |, ΔG ₂ = |G ₃ -G ₂ |, and ΔG ₁ = |G ₁ -G _1-1 |; then, a quantity obtained by adding up the totals of the elements in the subtraction quantity queue is calculated to obtain a quantity obtained by adding up the totals of the subtraction quantity queue;

Then, after determining the total sum of the subtraction queues of the discrete amount of the packet information of each grouping, the interference value reference of the current information segment is calculated. The calculation equation is:

In the equation, a is the interference value benchmark of the current information segment; It is the amount obtained by adding up the total of each element in the subtraction queue; e is the Euler number.

Furthermore, in step 3, a simulation is performed on the current information segment to obtain a simulated line on the Cartesian coordinate system as follows:

A Gauss-Newton method is used to perform a simulation on the current information segment to obtain a simulation line of the current information segment on a Cartesian coordinate system.

Furthermore, in step 4, the updated noise reduction threshold calculation equation is:

In the equation, _L1 is the noise reduction threshold after the current information segment is refreshed; _L0 is the noise reduction threshold before the refresh; W is the change speed of the current information segment; b is a predefined quantity, and e is the Euler number.

An optimized processing device for electronic information, comprising:

A display screen and a sampling device connected to the controller, wherein the sampling device is located on the object being measured and is used to sample electronic information of the object being measured and transmit it to the controller. The controller is used to process the collected electronic information of the object being measured and transmit the processed electronic information to the display screen for display;

The modules running on the controller include:

a change module for acquiring electronic information of the target under test and arranging it into an electronic information queue in the order of sampling time points, identifying the change value in the electronic information queue that is latest from the current information, and treating the information segment formed by the current information and the change value as the current information segment;

A reference module is used to calculate an interference value reference of the current information segment, use the interference value reference as a parameter input to a corresponding operation, and perform the corresponding operation to obtain a noise reduction threshold value for the current information segment;

a calculation module configured to perform a simulation on the current information segment to obtain a simulated line on a Cartesian coordinate system, calculate a value obtained by dividing the value by the average of the distances between the electronic information in the current information segment and the simulated line as the simulated value of the simulated line, and multiply the tangent of the angle between the simulated line and the X-axis of the Cartesian coordinate system by the simulated value as the change rate of the current information segment;

The refresh module is used to refresh the noise reduction threshold, use the refreshed noise reduction threshold as the threshold to apply the wavelet closed value noise reduction method to perform noise reduction on the current information segment, obtain the noise reduction information of the current information, and use the noise reduction information as the processed electronic information.

The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

If the change trend of the electronic information in the current information segment is close to linear, the wavelet closed-value denoising method with better fault tolerance can be used to perform denoising on the current information segment, thereby ensuring the accuracy of the data after denoising. In addition, by combining the interference value benchmark and change speed of the current information segment, the denoising threshold when performing the wavelet closed-value denoising method on the current information segment can be actively configured, which can improve the efficiency of the denoised electronic information while improving the accuracy of the obtained denoised electronic information, that is, the processed electronic information.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a partial flow chart of the method for optimizing processing of electronic information according to the present invention;

FIG2 is a schematic diagram of a portion of the structure of the device for optimizing processing of electronic information according to the present invention.

DETAILED DESCRIPTION

To make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely expressed below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without making creative work are all within the scope of protection of the present invention.

As shown in FIG1 , the present invention provides an optimization processing method for electronic information, including:

The sampling device samples the electronic information of the measured target and transmits it to the controller. The controller processes the collected electronic information of the measured target and transmits the processed electronic information to the display screen for display, thereby achieving the purpose of sampling and monitoring the electronic information;

The controller processes the electronic information of the detected target, including:

Step 1: Obtain electronic information of the target and arrange it into an electronic information queue in the order of sampling time points. Identify the latest change value from the current information in the electronic information queue. The information segment formed by the current information and the change value is regarded as the current information segment. The change value is the information point that is different from the overall change trend of the previous electronic information.

In this application, an electronic information queue is a queue of any type of corresponding electronic information sampled during the period when a sampling device samples the electronic information of a measured object, used to reflect the function and status of the measured object. The measured object can be a transistor, diode, or transformer, the sampling device can be a level sensor, power transmitter, etc., and the electronic information queue can be a level value queue or a power value queue. The electronic information is the level value or power value.

The sampling device samples the electronic information of the target at a set time interval according to a set sampling speed (such as a sampling speed of twice per second), thereby obtaining an electronic information queue.

In a preferred but non-limiting embodiment of the present invention, in step 1, the change value is an information point (information point is electronic information) in the electronic information queue that has a different change trend from the previous plurality of electronic information, and is used to segment the electronic information queue into a plurality of information segments with similar change trends. During operation, the target being measured is subject to the influence of a number of factors, such as external wind speed, wind force, humidity, etc., and the interaction between these factors causes the sampled electronic information queue to often exhibit a non-constant rate of change. However, within a relatively short period of time or a small operating range, the change of electronic information is close to a constant rate of change. Therefore, the present application uses the change value to identify information segments within the electronic information queue whose overall change trend is close to a constant rate of change.

In a preferred but non-limiting embodiment of the present invention, in step 1, the method for determining the latest change value from the current information in the electronic information queue includes:

Perform change value detection on the electronic information queue to obtain all change values in the electronic information queue, and take the change value with the smallest time interval between its corresponding sampling time point and the current time point as the latest change value from the current information in the electronic information queue.

In a preferred but non-limiting embodiment of the present invention, in step 1, after identifying the latest change value from the current message in the electronic message queue, the message segment between the change value and the current message is considered the current message segment. Detecting change values in this message segment can be accomplished using a change point finder.

Step 2: Calculate the interference value reference of the current information segment, use the interference value reference as a parameter for inputting the corresponding operation, and perform the corresponding operation to obtain the noise reduction threshold value of the current information segment;

In this application, the interference value benchmark is information used to reflect the size of the interference value in the current information segment. For example, if the interference value in the current information segment is not small, then the interference value benchmark of the current information segment is not small.

The noise reduction threshold is a parameter used to determine the effect of the wavelet closed-value noise reduction method on electronic information and the corresponding interference value when the wavelet closed-value noise reduction method is used to perform noise reduction processing. When the noise reduction threshold is not low, the wavelet closed-value noise reduction method is more sensitive to electronic information and can respond to information changes more efficiently, but it is also often more frequently affected by interference values; otherwise, when the noise reduction threshold is not high, the sensitivity to interference values can be reduced, but the response to dynamic changes in information is also relatively slow.

The wavelet closed-value denoising method is a method for performing denoising on an information stream that changes at a constant rate. Even though it has a high fault tolerance for each type of information when the target being measured is working, it is not suitable for non-constant rate changes of each type of information when the target being measured is working. The method for identifying the current information segment in this application can ensure that the changes in the electronic information in the current information segment are close to the constant rate changes, so that the wavelet closed-value denoising method can be used to perform denoising on the current information segment.

In a preferred but non-limiting embodiment of the present invention, in step 2, the predefined quantity is set to 12. After the interference value reference a of the current information segment is determined, the noise reduction threshold value L ₀ =12 ^a for the current information segment is used.

In a preferred but non-limiting embodiment of the present invention, in step 2, the method of calculating the interference value reference of the current information segment includes:

Step 2-1: Determine the optimal grouping size for grouping the current information segment. Use a natural number between 1 and the optimal grouping size as a standard size. Use each standard size as the grouping size for grouping the current information segment. Perform grouping on the current information segment several times to obtain grouping information for each grouping.

During the grouping of the current information segment, as the grouping amount increases, the grouping method will try to find more centroids in the current information segment to cut the information points more thoroughly, so as to grasp more distribution structures and patterns in the current information segment. If the interference value in the current information segment is not large, then the distribution structure and pattern grasped by the grouping method will be clearer. Therefore, this property can be used to perform multiple grouping processes on the current information segment, so that the interference value benchmark of the current information segment can be estimated based on the grouping information of each grouping.

In a preferred but non-limiting embodiment of the present invention, in step 2-1, the optimal grouping amount is the optimal number of groups when performing grouping on the current information segment, and the optimal grouping amount is determined using a cross-validation method;

Use the expectation maximization algorithm to group the current information segments;

After determining the optimal grouping quantity l when grouping the current information segment, a natural number between one and l can be used as a standard quantity. Here, the standard quantity includes one and l, that is, the standard quantity is the queue {1,2...l}.

Just as when it is determined that the optimal grouping quantity l when grouping the current information segment is five, the various values in the queue {1,2,3,4,5} are respectively regarded as the grouping quantities when grouping the current information segment, that is, the current information segment is grouped with a grouping quantity of one, a grouping quantity of two, a grouping quantity of three, a grouping quantity of four, and a grouping quantity of five, respectively, so as to obtain the grouping information of each grouping.

Step 2-2, calculate the average of the distances between the centroid and the nearest centroid after the random grouping is completed, and obtain the discrete amount of the grouping information of the random grouping;

Here, the discrete quantity is information that can reflect the discrete state of the groups obtained after the grouping is completed, and is used to estimate the role of the interference value in the current information segment. Just as after any grouping is completed, the distance between each centroid and the corresponding nearest centroid is not small, which means that the groups obtained after the grouping is completed are very discrete, which means that the distribution structure and method obtained during the grouping are very clear, which means that the interference value caused by the current information aggregation is not large.

In a preferred but non-limiting embodiment of the present invention, in step 2-2, the distance between any centroid after any grouping is achieved and the corresponding most adjacent centroid is the L2 norm.

In a preferred but non-limiting embodiment of the present invention, in step 2-2, the distance between the centroid and the nearest centroid is the global distance, and the method for determining the global distance is:

Obtain the nearest group of any group after any grouping is completed, calculate the average of the distances between the information points in the nearest group and the centroid of the nearest group, and divide the value obtained by one by the average as the grouping optimal value of the nearest group; multiply the grouping optimal value by the distance between the centroid of any group and the centroid of the nearest group as the global distance between the centroid of any group and the centroid of the nearest group;

That is, the global distance between the centroid of the jth group obtained after the kth grouping is achieved and the centroid of the most adjacent group of the jth group obtained after the kth grouping is achieved Here, is the distance between the centroid of the jth group obtained after the kth grouping is completed and the centroid of the most adjacent group of the jth group obtained after the kth grouping is completed, It is the optimal number of groups of the closest groupings of the jth grouping obtained after the kth grouping is completed;

Then, after determining the centroid of any group after any grouping is completed and the global distance between the centroid of the group and the nearest centroid of the group, the discrete amount of the grouping information of the group can be calculated, that is, the following equation can be calculated:

In the equation, _Gk is the discrete amount of grouping information of the kth grouping; is the distance between the centroid of the jth group obtained after the kth grouping is completed and the centroid of the most adjacent group of the jth group obtained after the kth grouping is completed; is the optimal number of groups of the closest groupings of the jth grouping obtained after the kth grouping is achieved; _pk is the number of groups obtained after the kth grouping is achieved.

In step 2-3, the discrete quantities of the grouped information of each group are subtracted pairwise to obtain a subtraction quantity queue, the total sum of the elements in the subtraction quantity queue is calculated, and the inverse value of the total sum is normalized to obtain the interference value benchmark of the current information segment.

In a preferred but non-limiting embodiment of the present invention, steps 2-3 specifically include:

Initially, a discrete quantity queue of group information obtained from the first grouping to the last grouping is defined as Y _G = {G ₁ , G ₂ , ...G ₁ }, where G ₁ , G ₂ , and G ₁ are discrete quantities of group information obtained when grouping the current information using a grouping size of one, a grouping size of two, and an optimal grouping size, respectively; then, a subtraction quantity queue ΔZ _G = {ΔG ₁ , ΔG ₂ , ...ΔG _1-1 } is calculated for the discrete quantity queue, where ΔG ₁ = |G ₂ -G ₁ |, ΔG ₂ = |G ₃ -G ₂ |, and ΔG ₁ = |G ₁ -G _1-1 |; then, a quantity obtained by adding up the totals of the elements in the subtraction quantity queue is calculated to obtain a quantity obtained by adding up the totals of the subtraction quantity queue;

Then, after determining the total sum of the subtraction queues of the discrete amount of the packet information of each grouping, the interference value reference of the current information segment is calculated. The calculation equation is:

In the equation, a is the interference value benchmark of the current information segment; It is the amount obtained by adding up the total of each element in the subtraction queue; e is the Euler number.

Step 3: Perform a simulation on the current information segment to obtain a simulated line on a Cartesian coordinate system (the horizontal axis represents the time point of the electronic information in the current information segment, and the vertical axis represents the value of the electronic information). The value obtained by dividing the value by the mean of the distance (L2 norm) between the electronic information in the current information segment and the simulated line is used as the simulated value of the simulated line. The value obtained by multiplying the tangent of the angle between the simulated line and the Cartesian x-axis by the simulated value is used as the change rate of the current information segment.

In a preferred but non-limiting embodiment of the present invention, in step 3, a method of performing a simulation on the current information segment to obtain a simulated line on a Cartesian coordinate system is as follows:

A Gauss-Newton method is used to perform a simulation on the current information segment to obtain a simulation line of the current information segment on a Cartesian coordinate system.

Next, after identifying the analog line of the current information segment, the tangent value of the angle between the analog line and the X-axis of the Cartesian system is used as the changing speed of the electronic information in the current information segment. Because the changing trends of each electronic information in the current information segment are close to a constant ratio, the tangent value of the angle between the identified analog line and the X-axis of the Cartesian system can represent the changing speed of the electronic information in the current information segment.

Since there are some simulation deviations when performing a simulation on the current information segment, the simulation value of the simulation line of the current information segment is regarded as the credibility of the tangent value of the angle between the simulation line and the X-axis of the Cartesian system, which can better ensure the accuracy of the change speed of the recognized current information segment.

Step 4, refresh the noise reduction threshold, use the refreshed noise reduction threshold as the threshold to apply the wavelet closed value noise reduction method to perform noise reduction on the current information segment, obtain the noise reduction information of the current information, and use the noise reduction information as the processed electronic information.

In a preferred but non-limiting embodiment of the present invention, in step 4, the updated noise reduction threshold value calculation equation is:

L ₁ =L ₀ *b ^1-eW ;

In the equation, _L1 is the noise reduction threshold after the current information segment is refreshed; _L0 is the noise reduction threshold before the refresh; W is the change speed of the current information segment; b is a predefined quantity, in this application b=12, and e is the Euler number.

Here, if the change speed of the current information segment is higher than zero, it means that the electronic information in the current information segment is gradually increasing, and a large noise reduction threshold must be set to respond to the changing trend of the electronic information in the current information segment. Otherwise, if the change speed of the current information segment is lower than zero, it means that the electronic information in the current information segment is gradually decreasing, and a small noise reduction threshold must be set to reduce the computing cost. The higher the value of W|, the higher the correction value of the noise reduction threshold before refresh.

After determining the refreshed noise reduction threshold, the noise reduction threshold can be used as the threshold when executing the wavelet closed value noise reduction method on the current information segment to obtain the noise reduction information of the current information, and the noise reduction information can be used as the processed electronic information.

As shown in FIG2 , the present invention provides an optimized processing device for electronic information, including:

A display screen and a sampling device connected to the controller. The sampling device is located on the target being measured. The sampling device is used to sample electronic information from the target being measured and transmit it to the controller. The controller is used to process the collected electronic information from the target being measured and transmit the processed electronic information to the display screen for display, thereby achieving the purpose of sampling and monitoring electronic information.

The modules running on the controller include:

a change module for acquiring electronic information of the target under test and arranging it into an electronic information queue in the order of sampling time points, identifying the change value in the electronic information queue that is latest from the current information, and treating the information segment formed by the current information and the change value as the current information segment;

A reference module is used to calculate an interference value reference of the current information segment, use the interference value reference as a parameter input to a corresponding operation, and perform the corresponding operation to obtain a noise reduction threshold value for the current information segment;

a calculation module configured to perform a simulation on the current information segment to obtain a simulated line on a Cartesian coordinate system, calculate a value obtained by dividing the value by the average of the distances between the electronic information in the current information segment and the simulated line as the simulated value of the simulated line, and multiply the tangent of the angle between the simulated line and the X-axis of the Cartesian coordinate system by the simulated value as the change rate of the current information segment;

The refresh module is configured to refresh the noise reduction threshold, use the refreshed noise reduction threshold as the threshold, and apply a wavelet closed-value noise reduction method to the current information segment to perform noise reduction, thereby obtaining noise reduction information of the current information and treating the noise reduction information as processed electronic information. The controller may be a single-chip microcomputer or a programmable logic controller (PLC).

The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

If the change trend of the electronic information in the current information segment is close to linear, the wavelet closed-value denoising method with better fault tolerance can be used to perform denoising on the current information segment, thereby ensuring the accuracy of the data after denoising. In addition, by combining the interference value benchmark and change speed of the current information segment, the denoising threshold when performing the wavelet closed-value denoising method on the current information segment can be actively configured, which can improve the efficiency of the denoised electronic information while improving the accuracy of the obtained denoised electronic information, that is, the processed electronic information.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not deviate from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims (9)

1. An optimization processing method for electronic information is characterized by comprising the following steps:

the sampling device samples the electronic information of the detected target and transmits the electronic information to the controller, and the controller performs treatment on the received electronic information of the detected target and transmits the treated electronic information to the display screen for display;

A method for the controller to process the electronic information of the detected object includes

Step 1, acquiring electronic information of a measured object, arranging the electronic information into an electronic information queue according to the sequence of sampling time points of the electronic information, identifying a variation value which is the latest from current information in the electronic information queue, and taking the current information and the variation value as an information segment;

step 2, calculating an interference value reference of the current information segment, taking the interference value reference as a parameter for inputting corresponding operation, and executing corresponding operation to obtain a noise reduction threshold of the current information segment;

step 3, performing a simulation on the current information segment once to obtain a simulation line on a Cartesian coordinate system, calculating a quantity obtained by dividing the mean value of the distances between the electronic information in the current information segment and the simulation line as a simulation quantity of the simulation line, and multiplying the tangent value of the included angle between the simulation line and the X axis of the Cartesian system by the simulation quantity to obtain a variation speed of the current information segment;

step 4, refreshing the noise reduction threshold, using the refreshed noise reduction threshold as a threshold to execute noise reduction on the current information segment by using a wavelet closed value noise reduction method, obtaining noise reduction information of the current information, and using the noise reduction information as treated electronic information;

In step 1, the variation value is an information point which is different from the variation trend of a plurality of previous electronic information in the electronic information queue and is used for cutting the electronic information queue into a plurality of information segments with similar variation trend;

In step 1, a method for identifying a latest variation value from current information in an electronic information queue includes:

detecting the variation value of the electronic information queue, obtaining the whole variation value in the electronic information queue, and taking the variation value with the minimum time interval between the same current time point and the corresponding sampling time point as the variation value with the latest time interval from the current information in the electronic information queue;

in step 1, after the latest fluctuation value from the current information in the electronic information queue is determined, the fluctuation value and the information segment between the current information are regarded as the current information segment.

2. The optimizing processing method for electronic information according to claim 1, wherein in step 2, a predefined amount is set to 12, and after the interference value reference a of the present information segment is recognized, the noise reduction threshold L ₀＝12^a of the present information segment is set.

3. The method for optimizing electronic information according to claim 2, wherein in step 2, the method for calculating the interference value reference of the nonce information piece includes:

Step 2-1, identifying the optimal grouping quantity when grouping the current information segment, taking the natural number from one to the optimal grouping quantity as a standard quantity, respectively taking each standard quantity as the grouping quantity when grouping the current information segment, and performing grouping treatment on the current information segment for a plurality of times to obtain grouping information of each grouping;

step 2-2, calculating the average of the distances between the centroid after random 1-time grouping is achieved and the nearest neighboring centroid, and obtaining the dispersion quantity of grouping information of random 1-time grouping;

And 2-3, performing subtraction on discrete amounts of packet information of each sub-packet to obtain a subtraction queue, calculating an amount obtained by adding total of each element in the subtraction queue, performing normalization processing on a inverse value of the amount obtained by adding total, and obtaining an interference value standard of the current information piece.

4. The optimizing processing method for electronic information according to claim 3, wherein in step 2-1, the optimal packet amount is an optimal packet number when performing the grouping of the pieces of the current information, the optimal packet amount being determined by using a cross-validation method;

Grouping the current information segments by using an expectation maximization algorithm;

After the optimal grouping amount l for grouping the pieces of nonce information is determined, a natural number from one to l can be used as a standard amount, where the standard amount contains one and l, i.e., the standard amount is the queue {1, 2..l }.

5. The method according to claim 4, wherein in step 2-2, the distance between the arbitrary centroid after the arbitrary 1-time grouping is achieved and the corresponding nearest neighboring centroid is L2 norm;

In step 2-2, the distance between the centroid and the nearest neighboring centroid is a global distance, and the method for identifying the global distance is as follows:

Obtaining the nearest-neighbor grouping of the random group after the random group is achieved for 1 time, calculating the average value of the distance between the information point in the nearest-neighbor grouping and the centroid of the nearest-neighbor grouping, and using a value obtained by dividing the average value as the optimal grouping quantity of the nearest-neighbor grouping;

I.e., the centroid of the j-th group obtained after the k-th group is achieved, and the global spacing between centroids of the nearest neighbor group of the j-th group obtained after the k-th group is achieved Here the number of the elements is the number,Is the centroid of the j-th grouping obtained after the k-th grouping is achieved, the distance between the centroids of the j-th grouping and the closest adjacent group obtained after the k-th grouping is achieved,The packet preference of the nearest neighbor packet of the j-th packet obtained after the k-th packet is achieved;

Then, after the center of mass of the random group is determined to be the center of mass of the random group after the random group is achieved for 1 time and the global distance between the centers of the nearest adjacent groups of the groups is the same, the discrete quantity of the grouping information of the random group can be calculated, namely the following equation is calculated:

In the equation, G _k is a discrete amount of packet information of the kth packet; The center of mass of the j-th grouping obtained after the k-th grouping is achieved, and the distance between the center of mass of the j-th grouping and the center of mass of the nearest adjacent grouping obtained after the k-th grouping is achieved; The optimal packet size of the nearest neighbor packet of the jth packet obtained after the kth packet is achieved, and p _k is the number of packets obtained after the kth packet is achieved.

6. The method for optimizing electronic information according to claim 5, wherein the steps 2-3 specifically include:

The discrete amount of packet information obtained by starting to group the first time to the last 1 time is defined as Y _G＝{G₁,G₂...G_l, where G ₁,G₂ and G _l are the discrete amounts of packet information obtained when the current information is subjected to grouping with the group amount being one and the group amount being two, respectively, the group amount being the optimal group amount;

Then, after the total addition of the number of the divided amounts of the packet information of each sub-packet is determined, the interference value reference of the current information segment is calculated, and the calculation equation is:

In the equation, a is the interference value reference of the current information segment; is the sum of the elements in the queue, e is the Euler number.

7. The method of claim 6, wherein in step 3, the method of performing a simulation on the current information segment to obtain a simulation line on a cartesian coordinate system comprises:

A simulation is performed on the current information segment by using a Gaussian-Newton method, and a simulation line of the current information segment on a Cartesian coordinate system is obtained.

8. The method according to claim 7, wherein in step 4, the operation equation of the refreshed noise reduction threshold is:

L₁＝L₀*b^1-eW;

In the equation, L ₁ is a threshold value for noise reduction after refreshing of the nonce information piece, L ₀ is a threshold value for noise reduction before refreshing, W is a fluctuation speed of the nonce information piece, b is a predefined quantity, and e is an euler number.

9. An electronic information-oriented optimization processing device, characterized by comprising:

the sampling device is used for sampling the electronic information of the detected target and transmitting the electronic information to the controller, and the controller is used for executing treatment on the received electronic information of the detected target and transmitting the treated electronic information to the display screen for display;

the modules running on the controller include:

the change module is used for acquiring the electronic information of the tested object, arranging the electronic information into an electronic information queue according to the sequence of sampling time points of the electronic information queue, identifying a change value which is the latest from the current information in the electronic information queue, and taking the current information and the change value as an information segment;

the reference module is used for calculating an interference value reference of the current information segment, taking the interference value reference as a parameter for inputting corresponding operation, and executing corresponding operation to obtain a noise reduction threshold value of the current information segment;

The operation module is used for performing one-time simulation on the current information segment to obtain a simulation line on a Cartesian coordinate system, calculating an amount obtained by dividing the mean value of the distances between the electronic information in the current information segment and the simulation line as a simulation amount of the simulation line, and multiplying the tangent value of the included angle between the simulation line and the X axis of the Cartesian system by the simulation amount to obtain a variation speed of the current information segment;

The refreshing module is used for refreshing the threshold value for noise reduction, performing noise reduction on the current information segment by using the wavelet closed value noise reduction method by taking the refreshed threshold value for noise reduction as the threshold value, acquiring noise reduction information of the current information, and taking the noise reduction information as treated electronic information;

the change value is an information point which is different from the change trend of a plurality of previous electronic information in the electronic information queue and is used for cutting the electronic information queue into a plurality of information segments with similar change trend;

The method for identifying the latest variation value from the current information in the electronic information queue comprises the following steps:

detecting the variation value of the electronic information queue, obtaining the whole variation value in the electronic information queue, and taking the variation value with the minimum time interval between the same current time point and the corresponding sampling time point as the variation value with the latest time interval from the current information in the electronic information queue;

After the latest variation value from the current information in the electronic information queue is identified, the variation value and the information section of the current information are used as the current information section.