Optimization processing method and device for electronic information

Abstract

The invention discloses an optimization processing method and device for electronic information, belongs to the technical field of information processing, and aims at reducing noise of a current information segment by using a wavelet closed value noise reduction method with better fault tolerance if the change trend of the electronic information in the current information segment is determined to be close to linearity. Therefore, the accuracy of the identified denoised data is ensured; according to the method, the noise reduction threshold value for executing the wavelet closed value noise reduction method on the current information segment is actively configured by combining the interference value reference and the variation speed of the current information segment, so that the accuracy of the obtained noise-reduced electronic information, namely the processed electronic information, can be improved while the efficiency of the noise-reduced electronic information is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of information processing, and in particular relates to an optimization processing method and device for electronic information. Background Art

[0002] 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.

[0003] 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

[0004] In order to solve the defects in the prior art, 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 executing the wavelet closed value denoising method on the current information segment is actively configured, so that the efficiency of the denoised electronic information can be improved while improving the accuracy of the obtained denoised electronic information, that is, the processed electronic information.

[0005] The present invention uses the following technical solutions.

[0006] A method for optimizing processing of electronic information, comprising:

[0007] The sampling device samples the electronic information of the measured object and transmits it to the controller, and the controller processes the collected electronic information of the measured object and transmits the processed electronic information to the display screen for display;

[0008] The controller processes the electronic information of the detected target, including:

[0009] Step 1, obtaining the electronic information of the target to be measured and arranging it into an electronic information queue according to the order of the sampling time points, identifying the latest change value from the current information in the electronic information queue, and treating the information segment formed by the current information and the change value as the current information segment;

[0010] Step 2, calculating the interference value reference of the current information segment, taking the interference value reference as a parameter input into the corresponding calculation, and performing the corresponding calculation to obtain the noise reduction threshold of the current information segment;

[0011] Step 3, a simulation is performed on the current information segment to obtain a simulated line on the Cartesian coordinate system, 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 is used as the simulated value of the simulated line, and a value obtained by multiplying the tangent value of the angle between the simulated line and the X-axis of the Cartesian system by the simulated value is used as the change speed of the current information segment;

[0012] 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.

[0013] 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.

[0014] Furthermore, in step 1, the method for determining the latest change value from the current information in the electronic information queue includes:

[0015] 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.

[0016] 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.

[0017] Furthermore, in step 2, the predefined amount is set to 12. After the interference value reference a of the current information segment is determined, the noise reduction threshold L of the current information segment is 0 =12 a .

[0018] Furthermore, in step 2, the method of calculating the interference value reference of the current information segment includes:

[0019] Step 2-1, determine the optimal grouping amount when performing grouping on the current information segment, take a natural number between 1 and the optimal grouping amount as a standard amount, take each standard amount as the grouping amount when performing grouping on the current information segment, perform grouping processing on the current information segment several times, and obtain grouping information of each grouping;

[0020] 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;

[0021] Step 2-3, perform pairwise subtraction on the discrete quantities of the grouping information of each grouping to obtain a subtraction quantity queue, calculate the total sum of each element in the subtraction quantity queue, perform standardization on the inverse value of the total sum, and obtain the interference value benchmark of the current information segment.

[0022] 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;

[0023] Use the expectation maximization algorithm to group the current information segments;

[0024] 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}.

[0025] Furthermore, in step 2-2, the distance between any centroid after any grouping is achieved and the corresponding most adjacent centroid is the L2 norm.

[0026] 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:

[0027] 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 average by one to obtain the value as the optimal grouping value of the nearest group; multiply the optimal grouping value by the distance between the centroid of any group and the centroid of the nearest group to obtain the value as the global distance between the centroid of any group and the centroid of the nearest group;

[0028] That is, the global distance between the centroid of the jth group obtained after the kth grouping is achieved and the centroid of the closest 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 closest 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 completed;

[0029] 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 grouping can be calculated, that is, the following equation can be calculated:

[0030]

[0031] In the equation, G k 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 closest 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 groupings obtained after the kth grouping is completed; p k is the number of groups obtained after the kth achievement.

[0032] Furthermore, steps 2-3 specifically include:

[0033] Initially, define the discrete queue of packet information obtained from the first packet to the last packet as Y G = {G 1 , G 2 ...G l}, where G 1 , G 2 and G l The discrete amount of grouped information obtained when the current information is grouped by using the grouping amount of one, the grouping amount of two, and the grouping amount of the optimal grouping amount; then the subtraction amount queue ΔZ of the discrete amount queue is calculated G ={ΔG 1 , ΔG 2 ...ΔG l-1}, where ΔG 1 =|G 2 -G 1 |,ΔG 2 =|G 3 -G 2 |,ΔG l =|G l -G l-1 |, then calculate the amount obtained by adding up the totals of the elements in the subtraction queue, thereby obtaining the amount obtained by adding up the totals of the subtraction queue;

[0034] 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, and the calculation equation is:

[0035]

[0036] In the equation, a is the interference value reference of the current information segment; It is the sum of the totals of the elements in the subtraction queue; e is the Euler number.

[0037] Furthermore, in step 3, a method of performing a simulation on the current information segment to obtain a simulated line on the Cartesian coordinate system is:

[0038] 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.

[0039] Furthermore, in step 4, the updated noise reduction threshold calculation equation is:

[0040]

[0041] In the equation, L 1 is the refreshed noise reduction threshold of the current information segment; L 0 is the threshold for noise reduction before refreshing; W is the speed of change of the current information segment; b is a predefined quantity, and e is the Euler number.

[0042] An optimization processing device for electronic information, comprising:

[0043] A display screen and a sampling device connected to the controller, the sampling device is arranged on the measured object, the sampling device is used to sample the electronic information of the measured object and transmit it to the controller, and the controller is used to process the collected electronic information of the measured object and transmit the processed electronic information to the display screen for display;

[0044] The modules running on the controller include:

[0045] A change module is used to obtain the electronic information of the measured target and arrange it into an electronic information queue according to the order of the sampling time points, identify the latest change value from the current information in the electronic information queue, and regard the information segment formed by the current information and the change value as the current information segment;

[0046] A reference module is used to calculate the interference value reference of the current information segment, take the interference value reference as a parameter input into the corresponding operation, and perform the corresponding operation to obtain the noise reduction threshold of the current information segment;

[0047] A calculation module, which is used 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 value of the angle between the simulated line and the X-axis of the Cartesian system by the simulated value to obtain a value as the change speed of the current information segment;

[0048] A 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.

[0049] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0050] If the change trend of the electronic information in the recognized 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 recognized denoised data; and 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

[0051] Figure 1 It is a partial flow chart of the optimization processing method for electronic information described in the present invention;

[0052] Figure 2 It is a partial structural diagram of the optimization processing device for electronic information described in the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely expressed in combination with the 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. According to the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the protection scope of the present invention.

[0054] like Figure 1 As shown, the optimization processing method for electronic information described in the present invention includes:

[0055] 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;

[0056] The controller processes the electronic information of the detected target, including:

[0057] Step 1, obtaining the electronic information of the target to be tested and arranging it into an electronic information queue according to the order of the sampling time points, identifying the latest change value from the current information in the electronic information queue, treating the information segment formed by the current information and the change value as the current information segment, and the change value is an information point that is different from the overall change trend of the previous electronic information;

[0058] In this application, the electronic information queue is a queue of any corresponding electronic information sampled during the period when the sampling device samples the electronic information of the measured target, which is used to reflect the function and status of the measured target. The measured target can be a transistor, a diode or a transformer, the sampling device can be a level sensor, a 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 the power value.

[0059] The sampling device samples the electronic information of the target under test at a set sampling speed (such as a sampling speed of twice per second) within a set time interval, thereby obtaining an electronic information queue.

[0060] 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 is different from the change trend of the previous electronic information, which is used to cut the electronic information queue into several information segments with similar change trends. During the operation of the measured target, it will be affected by several factors, such as external wind speed, wind force, humidity, etc., and the interaction between several acting factors causes the sampled electronic information queue to often show a non-constant ratio change. However, the change of electronic information is close to a constant ratio change in a short time or a small operating range. Therefore, the present application uses the change value to identify the information segment whose overall change trend in the electronic information queue is close to the constant ratio change.

[0061] In a preferred but non-limiting embodiment of the present invention, in step 1, the method for identifying the latest change value from the current information in the electronic information queue includes:

[0062] 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.

[0063] In a preferred but non-limiting embodiment of the present invention, in step 1, after identifying the latest change value from the current information in the electronic information queue, the information segment between the change value and the current information is regarded as the current information segment. The change value detection for the information segment can be achieved by using a change point finder.

[0064] Step 2, calculating the interference value reference of the current information segment, taking the interference value reference as a parameter input into the corresponding calculation, and performing the corresponding calculation to obtain the noise reduction threshold of the current information segment;

[0065] In the present 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.

[0066] The denoising threshold is a parameter used to determine the effect of the wavelet closed-value denoising method on electronic information and the corresponding interference value when the wavelet closed-value denoising method is used to perform denoising processing. When the denoising threshold is not low, the wavelet closed-value denoising method is more sensitive to electronic information and can respond to information changes more efficiently, but it is also more likely to be affected by interference values; otherwise, when the denoising threshold is not high, the sensitivity to interference values ​​can be reduced, but the response to dynamic changes in information is also relatively slow.

[0067] The wavelet closed-value denoising method is a method for performing denoising on information streams that change 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.

[0068] In a preferred but non-limiting embodiment of the present invention, in step 2, the predefined amount is set to 12, and after the interference value reference a of the current information segment is determined, the noise reduction threshold L of the current information segment is used. 0 =12 a .

[0069] In a preferred but non-limiting embodiment of the present invention, in step 2, the method for calculating the interference value reference of the current information segment includes:

[0070] Step 2-1, determine the optimal grouping amount when performing grouping on the current information segment, take a natural number between 1 and the optimal grouping amount as a standard amount, take each standard amount as the grouping amount when performing grouping on the current information segment, perform grouping processing on the current information segment several times, and obtain grouping information of each grouping;

[0071] 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 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, the distribution structure and pattern grasped by the grouping method will be clearer. Therefore, this property can be used to perform several 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.

[0072] 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;

[0073] Use the expectation maximization algorithm to group the current information segments;

[0074] 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}.

[0075] Just as when it is determined that the optimal grouping amount l when performing grouping on the current information segment is five, the various values ​​in the queue {1,2,3,4,5} are respectively regarded as the grouping amounts when performing grouping on the current information segment, that is, the current information segment is grouped with grouping amounts of one, two, three, four and five, respectively, so as to obtain the grouping information of each grouping.

[0076] 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;

[0077] 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 mode obtained during the grouping are very clear, which means that the interference value caused by the current information aggregation is not large.

[0078] 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.

[0079] 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 identifying the global distance is:

[0080] 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 average by one to obtain the value as the optimal grouping value of the nearest group; multiply the optimal grouping value by the distance between the centroid of any group and the centroid of the nearest group to obtain the value as the global distance between the centroid of any group and the centroid of the nearest group;

[0081] That is, the global distance between the centroid of the jth group obtained after the kth grouping is achieved and the centroid of the closest 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 closest 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 completed;

[0082] 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 grouping can be calculated, that is, the following equation can be calculated:

[0083]

[0084] In the equation, G k 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 closest 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 groupings obtained after the kth grouping is completed; p k is the number of groups obtained after the kth achievement.

[0085] Step 2-3, perform pairwise subtraction on the discrete quantities of the grouping information of each grouping to obtain a subtraction quantity queue, calculate the total sum of each element in the subtraction quantity queue, perform standardization on the inverse value of the total sum, and obtain the interference value benchmark of the current information segment.

[0086] In a preferred but non-limiting embodiment of the present invention, steps 2-3 specifically include:

[0087] Initially, define the discrete queue of packet information obtained from the first packet to the last packet as Y G = {G 1 , G 2 ...G l}, where G 1 , G 2and G l The discrete amount of grouped information obtained when the current information is grouped by using the grouping amount of one, the grouping amount of two, and the grouping amount of the optimal grouping amount; then the subtraction amount queue ΔZ of the discrete amount queue is calculated G ={ΔG 1 , ΔG 2 ...ΔG l-1}, where ΔG 1 =|G 2 -G 1 |,ΔG 2 =|G 3 -G 2 |,ΔG l =|G l -G l-1 |, then calculate the amount obtained by adding up the totals of the elements in the subtraction queue, thereby obtaining the amount obtained by adding up the totals of the subtraction queue;

[0088] 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, and the calculation equation is:

[0089]

[0090] In the equation, a is the interference value reference of the current information segment; It is the sum of the totals of the elements in the subtraction queue; e is the Euler number.

[0091] Step 3, perform a simulation on the current information segment to obtain a simulated line on the Cartesian coordinate system (the horizontal axis is the time point of the electronic information in the current information segment, and the vertical axis is the value of the electronic information), calculate one divided by the average of the distance (L2 norm) 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 value of the angle between the simulated line and the X-axis of the Cartesian system by the simulated value to obtain the value as the change speed of the current information segment;

[0092] 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:

[0093] 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.

[0094] 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 trend of each electronic information in the current information segment is close to a constant ratio change, 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.

[0095] Then, because 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.

[0096] 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.

[0097] In a preferred but non-limiting embodiment of the present invention, in step 4, the updated noise reduction threshold value operation equation is:

[0098] L 1 =L 0 *b 1-eW ;

[0099] In the equation, L 1 is the refreshed noise reduction threshold of the current information segment; L 0 is the threshold for noise reduction before refreshing; W is the speed of change of the current information segment; b is a predefined quantity, in this application b=12, and e is the Euler number.

[0100] Here, if the changing speed of the current information segment is higher than zero, it means that the electronic information in the current information segment is gradually changing, and a large noise reduction threshold should be set to respond to the changing trend of the electronic information in the current information segment. Otherwise, if the changing 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 should 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.

[0101] 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.

[0102] like Figure 2 As shown, the optimization processing device for electronic information described in the present invention includes:

[0103] A display screen and a sampling device connected to the controller, the sampling device is arranged on the measured object, the sampling device is used to sample the electronic information of the measured object and transmit it to the controller, the controller is used to process the collected electronic information of the measured object and transmit the processed electronic information to the display screen for display, so as to achieve the purpose of sampling and monitoring of electronic information;

[0104] The modules running on the controller include:

[0105] A change module is used to obtain the electronic information of the measured target and arrange it into an electronic information queue according to the order of the sampling time points, identify the latest change value from the current information in the electronic information queue, and regard the information segment formed by the current information and the change value as the current information segment;

[0106] A reference module, which is used to calculate the interference value reference of the current information segment, take the interference value reference as a parameter input into the corresponding operation, and perform the corresponding operation to obtain the noise reduction threshold of the current information segment;

[0107] A calculation module, which is used 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 value of the angle between the simulated line and the X-axis of the Cartesian system by the simulated value to obtain a value as the change speed of the current information segment;

[0108] The refresh module is used to refresh the noise reduction threshold, use the refreshed noise reduction threshold as the threshold to perform noise reduction on the current information segment using the wavelet closed value noise reduction method, obtain the noise reduction information of the current information, and use the noise reduction information as the processed electronic information. The controller can be a single chip microcomputer or a PLC.

[0109] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0110] If the change trend of the electronic information in the recognized 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 recognized denoised data; and 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.

[0111] 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 relevant 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

1. A method for optimizing processing of electronic information, characterized in that: include: The sampling device samples the electronic information of the measured object and transmits it to the controller, and the controller 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, obtaining the electronic information of the target to be measured and arranging it into an electronic information queue according to the order of the sampling time points, identifying the latest change value from the current information in the electronic information queue, and treating the information segment formed by the current information and the change value as the current information segment; Step 2, calculating the interference value reference of the current information segment, taking the interference value reference as a parameter input into the corresponding calculation, and performing the corresponding calculation to obtain the noise reduction threshold of the current information segment; Step 3, a simulation is performed on the current information segment to obtain a simulated line on the Cartesian coordinate system, 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 is used as the simulated value of the simulated line, and a value obtained by multiplying the tangent value of the angle between the simulated line and the X-axis of the Cartesian 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.

2. The optimization processing method for electronic information according to claim 1, characterized in that: In step 1, the change value is an information point in the electronic information queue that is different from the change trend of the previous electronic information, and is used to cut the electronic information queue into several information segments with similar change trends; In step 1, the method for determining the latest change value from the current information in the electronic information queue includes: Performing change value detection on the electronic information queue to obtain all change values ​​in the electronic information queue, and taking 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 step 1, after the latest change value from the current information in the electronic information queue is identified, the information segment between the change value and the current information is regarded as the current information segment.

3. The optimization processing method for electronic information according to claim 2, characterized in that: In step 2, the predefined value is set to 12. After the interference value reference a of the current information segment is determined, the noise reduction threshold value L0 of the current information segment is L0 = 12. a .

4. The optimization processing method for electronic information according to claim 3, characterized in that: In step 2, the method of calculating the interference value reference of the current information segment includes: Step 2-1, determine the optimal grouping amount when performing grouping on the current information segment, take a natural number between 1 and the optimal grouping amount as a standard amount, take each standard amount as the grouping amount when performing grouping on the current information segment, perform grouping processing on the current information segment several times, and obtain 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; Step 2-3, perform pairwise subtraction on the discrete quantities of the grouping information of each grouping to obtain a subtraction quantity queue, calculate the total sum of each element in the subtraction quantity queue, perform standardization on the inverse value of the total sum, and obtain the interference value benchmark of the current information segment.

5. The optimization processing method for electronic information according to claim 4, characterized in that: 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}.

6. The optimization processing method for electronic information according to claim 5, characterized in that: In step 2-2, the distance between any centroid after any grouping is completed and the corresponding nearest centroid is the L2 norm; 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 average by one to obtain the value as the optimal grouping value of the nearest group; multiply the optimal grouping value by the distance between the centroid of any group and the centroid of the nearest group to obtain the value 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 closest 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 closest 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 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 grouping can be calculated, that is, the following equation can be calculated: In the equation, G k 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 closest 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 groupings obtained after the kth grouping is completed; p k is the number of groups obtained after the kth achievement.

7. The optimization processing method for electronic information according to claim 6, characterized in that: Steps 2-3 specifically include: Initially, define the discrete queue of packet information obtained from the first packet to the last packet as Y G = {G1, G2...G l }, where G1, G2 and G l The discrete amount of grouped information obtained when the current information is grouped by using the grouping amount of one, the grouping amount of two, and the grouping amount of the optimal grouping amount; then the subtraction amount queue ΔZ of the discrete amount queue is calculated G ={ΔG1, ΔG2...ΔG l-1 }, here, ΔG1=|G2-G1|, ΔG2=|G3-G2|, ΔG l =|G l -G l-1 |, then calculate the amount obtained by adding up the totals of the elements in the subtraction queue, thereby obtaining the amount obtained by adding up the totals of the subtraction queue; Next, after determining the amount obtained by adding up the total amount of the subtraction amount queue of the discrete amount of the packet information of each grouping, 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; It is the sum of the totals of the elements in the subtraction queue; e is the Euler number.

8. The optimization processing method for electronic information according to claim 7, characterized in that: In step 3, a simulation is performed on the current information segment to obtain a simulation 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.

9. The optimization processing method for electronic information according to claim 8, characterized in that: 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 speed of change of the current information segment; b is a predefined quantity, and e is the Euler number.

10. An optimization processing device for electronic information, characterized in that: include: A display screen and a sampling device connected to the controller, the sampling device is arranged on the measured object, the sampling device is used to sample the electronic information of the measured object and transmit it to the controller, and the controller is used to process the collected electronic information of the measured object and transmit the processed electronic information to the display screen for display; The modules running on the controller include: A change module is used to obtain the electronic information of the measured target and arrange it into an electronic information queue according to the order of the sampling time points, identify the latest change value from the current information in the electronic information queue, and regard the information segment formed by the current information and the change value as the current information segment; A reference module is used to calculate the interference value reference of the current information segment, take the interference value reference as a parameter input into the corresponding operation, and perform the corresponding operation to obtain the noise reduction threshold of the current information segment; A calculation module, which is used 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 value of the angle between the simulated line and the X-axis of the Cartesian system by the simulated value to obtain a value as the change speed of the current information segment; A 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.

Images