Integrated digital control system for heat treatment of fastener

Abstract

The invention relates to the technical field of identification control, in particular to a fastener heat treatment integrated digital control system which comprises a process sequence number setting module, a graph code analysis module, a parameter instruction generation module, a temperature zone driving judgment module and a state autonomous response module. According to the method, the fastener category and the thermal process section sequence number are subjected to combined coding and embedded into the graph code to construct the structured recognition pattern, clear identification and automatic recognition of the thermal process section sequence can be achieved, the structured sequence number is automatically extracted in combination with graph code image analysis, and the section sequence index result is generated; an instruction index relation is established through multi-section target parameter aggregation to form a structural body array, a response marking system is established in combination with temperature real-time acquisition and tolerance zone comparison, the abnormal deviation state in the processing process can be dynamically recognized, and autonomous cooling response is implemented based on the temperature deviation frequency; and the process continuity of system operation, the accuracy of a control instruction and the stability of temperature zone execution are comprehensively improved.

Description

Technical Field

[0001] This invention relates to the field of identification and control technology, and in particular to a digital control system for integrated heat treatment of fasteners. Background Technology

[0002] The field of identification and control technology involves using image recognition, barcode reading, visual perception, and radio frequency identification to acquire and analyze the status information of items, and based on this, to achieve equipment operation scheduling, production process control, quality tracking, and data management. It is widely used in system engineering projects such as production line informatization, quality tracking, and intelligent scheduling. Among these, the digital control system for fastener heat treatment refers to the process of controlling and managing the heat treatment process of fasteners such as bolts and nuts by collecting workpiece identification through identification devices and combining this with heat treatment process requirements. Typically, barcodes or QR codes are used to identify each batch of fasteners. A barcode reader acquires this identification information, matches it with heat treatment parameters through a database, and then the control unit controls the specific processes such as heating, cooling, and heat preservation, thus completing the digitization and controllability of the heat treatment process.

[0003] In existing fastener heat treatment processes, there is a lack of coding design for the heat treatment segment structure, making it difficult to achieve fine mapping of segmented control under complex process combinations. In the process of matching heat treatment parameters through the database, there are problems such as loose instruction structure and strong dependence on parameter calls. It is easy to cause instruction errors or logical confusion due to information chain breaks. Moreover, in terms of temperature control, it relies on simple upper and lower limit thresholds set externally and lacks a continuous discrimination mechanism for temperature fluctuations. It cannot actively adjust the treatment measures according to the real-time temperature deviation trend. For example, it cannot trigger control operations when the temperature is overheated for a long time but the fluctuation is not severe, resulting in sluggish response in the heat treatment process, aggravated energy consumption fluctuations, and distorted quality tracking. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a digital control system for integrated heat treatment of fasteners.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a digital control system integrating fastener heat treatment includes:

[0006] The process sequence number setting module obtains the fastener category and the corresponding hot process segment sequence number, sets an independent integer combination sequence number, embeds the combination sequence number into the process drawing code to construct a structured recognition pattern, and obtains the fastener segment sequence identification code.

[0007] The image code parsing module collects the image code of the fasteners entering the furnace and extracts the corresponding structured serial number according to the fastener segment sequence identifier code, counts the corresponding process segment combination index, and generates the thermal process segment sequence index result.

[0008] The parameter instruction generation module reads the corresponding process segment number, target temperature point and duration point according to the thermal process segment sequence index result, forms independent control logic in sequence, encapsulates it into the form of a structure array, and generates a control instruction structure set.

[0009] The temperature zone drive judgment module collects the real-time temperature of the fastener in the process section based on the control command structure set, marks whether the temperature is within the temperature zone tolerance zone of the corresponding section, determines whether to trigger a control action, and generates a process section temperature zone response mark set.

[0010] The autonomous response module counts the number of temperature offsets in each segment based on the set of temperature response markers for the process segment. When the number of offsets exceeds the cooling delay threshold, it performs a cooling operation and records the status, and then compiles and generates an integrated control record for fastener heat treatment.

[0011] As a further embodiment of the present invention, the fastener segment sequence identifier encoding includes a process category label, a segment sequence integer code, and a structured graphic code embedding index; the thermal process segment sequence index result includes a structured segment sequence mapping relationship, a segment sequence combination index value, and a process segment associated parameter index; the control instruction structure set includes a segment sequence parameter structure array, a target temperature control parameter set, and a loading order logic index; the process segment temperature zone response mark set includes a temperature zone judgment mark, an out-of-tolerance response mark record, and a material temperature difference tolerance label; and the fastener heat treatment integrated control record includes a process segment status mark table, a cooling trigger log, and temperature offset statistics.

[0012] As a further aspect of the present invention, the process sequence number setting module includes:

[0013] The process segment extraction submodule determines the fastener category, reads the corresponding hot process segment sequence number from the process database, and matches the corresponding number of each segment in sequence. By judging whether the hot process segment number matches the category, it filters all the corresponding hot process segment sequence numbers and generates a hot process segment number sequence.

[0014] The combined sequence number operation submodule extracts the intermediate field information of each number according to the thermal process section number sequence, sorts and compares the numbers, confirms the distinguishable coding segments, classifies the numbers by combining the clustering characteristics of the numerical values ​​in the sequence, and establishes independent combined sequence numbers.

[0015] The structure diagram code construction submodule adjusts the sub-category number according to the independent combination sequence number and the fastener main category code, sub-category code and sub-category number, and completes the field structure reorganization by corresponding with the combination sequence number. It also performs duplicate verification and number position verification to obtain the fastener segment sequence identifier code.

[0016] As a further aspect of the present invention, the image code parsing module includes:

[0017] The image acquisition submodule obtains the fastener segment sequence identification code, acquires the image corresponding to the identification area on the surface of the fastener entering the furnace, reads the image data stream and performs image grayscale conversion processing, performs tilt correction processing on the QR code image area, and obtains a structured image array.

[0018] The structure sequence number parsing submodule extracts the structured process code from the QR code based on the structured image array, splits the main category, sub-category, fine category and combination sequence number, performs validity verification operation to determine whether there is code length abnormality or non-matching structure, and performs field reconstruction operation to obtain the parsed structure sequence number value.

[0019] The segment sequence statistics and verification submodule performs a matching query operation based on the combined sequence number in the parsed structure sequence number value, establishes an index column for each segment sequence number field in order, and completes the validity confirmation of the segment group based on the sequence continuity check and fluctuation judgment, thus obtaining the thermal process segment sequence index result.

[0020] As a further aspect of the present invention, the parameter instruction generation module includes:

[0021] The process parameter extraction submodule reads the process segment parameters corresponding to each segment number according to the segment set in the thermal process segment sequence index result, establishes a one-to-one correspondence between process segments and parameter values, calculates and obtains the segment number parameter deviation judgment value, and generates a set of thermal segment parameter deviation values.

[0022] The instruction structure encapsulation submodule constructs a structured process parameter unit body based on the set of hot section parameter deviation values, generates a unique segment code identifier field for each structure body, encapsulates all segment parameter units through a structure array, establishes a segment sequence structure table, and obtains the process parameter structure array.

[0023] The control sequence index submodule rearranges the sequence numbers of each segment structure and marks the index numbers according to the process parameter structure array, identifies and reconstructs discontinuous segment numbers, constructs a mapping between segment order and control index, assigns sequence numbers to the sequence field according to the loading order, and establishes a control instruction structure set.

[0024] As a further aspect of the present invention, the temperature zone driving determination module includes:

[0025] Based on the control instruction structure set, the temperature acquisition submodule determines that the current process segment is in the execution state, acquires the real-time temperature value of the fastener surface, and records it as a temperature vector array according to the sampling time sequence. Each sampled value is assigned a corresponding timestamp identifier to obtain the real-time temperature record array.

[0026] The temperature zone comparison submodule is based on each sampled value in the real-time temperature record array and confirms the material type of the current segment according to the segment number of the structure. It then checks and determines the temperature zone tolerance zone, compares the target temperature range with the sampled value range, determines whether all temperature values ​​in the sampled data fall within the target range, groups and marks the determination results and archives them, summarizes the comparison of all sampled points, and obtains the segment temperature deviation trend record.

[0027] The action triggering submodule records the temperature deviation trend of each segment, converts the results of the segment marker array into status identifier bits, and determines whether the current segment meets the normal process conditions. If the status is determined to be abnormal, it is updated to the abnormal handling mode, and the response instruction set is written synchronously to generate the process segment temperature zone response marker set.

[0028] As a further aspect of the present invention, the state autonomous response module includes:

[0029] The offset statistics submodule performs segment division on the sampling points in sequence according to the response status identifier records of each segment in the temperature zone response marker set of the process segment, counts the cumulative number of valid offsets for each segment, stores the offset counts in correspondence with the segment sequence number, and obtains the segment offset count distribution data.

[0030] The cooling control submodule compares the segment offset number distribution data with the cooling delay threshold, and according to the process settings, it retrieves the response flag status and segment duration fields, confirms the current operating status, writes and updates those that meet the cooling triggering requirements, sets the cooling response flag to the active state, and obtains the segment cooling response status record.

[0031] The record generation submodule constructs a structured record unit in the order of segment numbering based on the segment cooling response status record, combines all segment control information, and uniformly encodes and marks the content of each response status to complete the encapsulation and classification of control behavior, and establishes an integrated control record for fastener heat treatment.

[0032] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0033] In this invention, by combining and encoding the fastener category with the sequential number of the thermal process segment and embedding it into the graphic code to construct a structured identification pattern, clear identification and automatic recognition of the heat treatment segment sequence can be achieved. Combined with graphic code image analysis, the structured sequence number is automatically extracted and a segment sequence index result is generated, which can effectively support the accuracy and logical integrity of subsequent parameter generation. Then, by aggregating multiple target parameters, an instruction index relationship is established to form a structure array, ensuring the dependency-free execution of control logic. Combined with real-time temperature acquisition and tolerance band comparison to establish a response marking system, abnormal deviation states in the processing can be dynamically identified and autonomous cooling responses can be implemented based on the number of temperature deviations. This gives the heat treatment process the comprehensive characteristics of precise process identification, orderly segment control, autonomous temperature control decision-making, and data-driven abnormal response, comprehensively improving the process continuity of system operation, the accuracy of control instructions, and the stability of temperature zone execution. Attached Figure Description

[0034] Figure 1 This is a system flowchart of the present invention;

[0035] Figure 2 This is a flowchart of the process sequence number setting module for the present invention;

[0036] Figure 3 This is a flowchart of the image and code parsing module of the present invention;

[0037] Figure 4 This is a flowchart of the parameter instruction generation module of the present invention;

[0038] Figure 5 This is a flowchart of the temperature zone driving judgment module of the present invention;

[0039] Figure 6 This is a flowchart of the state autonomous response module of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0041] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0042] Please see Figure 1 The integrated digital control system for fastener heat treatment includes:

[0043] The process sequence number setting module obtains the fastener category and the corresponding hot process segment sequence number, sets an independent integer combination sequence number, embeds the combination sequence number into the process drawing code (8-digit process code: the first 2 digits are the main category + 3 digits are the sub-category + 3 digits are the sub-detail) to construct a structured recognition pattern, and obtains the fastener segment sequence identification code;

[0044] The image code parsing module collects images of fasteners entering the furnace based on the fastener segment sequence identifier code, extracts the corresponding structured sequence number through image parsing (processed using the ISO / IEC 15415 QR code parsing algorithm), performs data validity verification, compiles the corresponding process segment combination index, and generates the thermal process segment sequence index result.

[0045] The parameter instruction generation module reads the corresponding process segment number, target temperature point and duration point from the heat treatment parameter set segment by segment according to the thermal process segment sequence index result. It aggregates multiple target parameters in sequence to form dependency-free control logic, encapsulates it in the form of a structure array, and establishes an index relationship for the instruction loading order to generate a control instruction structure set.

[0046] The temperature zone drive judgment module is based on the control command structure set. It collects the real-time temperature of the fastener in the process section and compares it with the temperature zone tolerance zone of the corresponding section (set according to the fastener material type, such as carbon steel quenching ±15℃, alloy steel ±10℃, etc.). It marks whether the temperature is within the range and judges whether to trigger the control action according to the comparison result (if not, the control action is triggered) and generates a set of process section temperature zone response marks.

[0047] The autonomous response module counts the number of temperature deviations in each segment based on the temperature zone response mark set of the process segment (three consecutive sampling points (sampling interval of 2s) exceeding the temperature gauge is considered one valid deviation). When the number of deviations exceeds the cooling delay threshold (cooling is triggered if the temperature exceeds the limit for 30 seconds), the module executes the cooling operation and records the status. It also organizes and marks all process segments to generate an integrated control record for fastener heat treatment.

[0048] The fastener segment sequence identifier code includes process category label, segment sequence integer code, and structured graphic code embedding index. The thermal process segment sequence index result includes structured segment sequence mapping relationship, segment sequence combination index value, and process segment associated parameter index. The control instruction structure set includes segment sequence parameter structure array, target temperature control parameter set, and loading order logic index. The process segment temperature zone response mark set includes temperature zone judgment mark, out-of-tolerance response mark record, and material temperature difference tolerance label. The fastener heat treatment integrated control record includes process segment status mark table, cooling trigger log, and temperature offset statistics.

[0049] Please see Figure 2 The process sequence number setting module includes:

[0050] The process segment extraction submodule determines the fastener category, reads the corresponding hot process segment sequence number from the process database, and matches the corresponding number of each segment in sequence. By judging whether the hot process segment number matches the category, it filters all the corresponding hot process segment sequence numbers and generates a hot process segment number sequence.

[0051] Based on fastener categories, it is necessary to first collect the category classification codes and corresponding process segment sequence numbers defined in the standard parts database. For example, hexagonal bolts correspond to main category code 01 and subcategory code 001, with their thermal process segment sequence numbers being T01 to T05. During execution, the actual fastener code must be used as an index to match and filter fields in the database. If a category has multiple sets of thermal process segment numbers, the numbering segments need to be split. The first and last segments of the number are extracted using string splitting as the start and end segment numbers, and mapped to an integer sequence. A set of comparable numbers is formed. Then, the main category field of the fastener is compared with the main category field of the corresponding number of the thermal process section. If they are consistent, the corresponding number is retained; otherwise, the information of that section is removed. At the same time, the number sequence is sorted in ascending order to eliminate interference from duplicate numbers and abnormal section numbers. For example, for the main category 01 and subcategory 002 of "internal hex screw", the thermal process section numbers are T02 to T06. The numbers T02, T03, T04, T05 and T06 need to be extracted in sequence to form the number sequence, and finally the thermal process section number sequence is obtained.

[0052] The combined sequence number operation submodule extracts the intermediate field information of each number according to the thermal process section number sequence, sorts and compares the numbers, confirms the distinguishable coding segments, classifies the numbers by combining the clustering characteristics of the numerical values ​​in the sequence, and establishes independent combined sequence numbers.

[0053] After obtaining the thermal process section number sequence, the structure of the number field of each section number needs to be parsed. For example, "03" is the key field in the structure of number T03. It is uniformly extracted as an intermediate field parameter. By judging the numerical interval of each intermediate field, if the numerical difference between consecutive numbers is greater than 1, it is classified into an independent section group. Then, the relative positional relationship between the sections is marked. In this process, the number sequence needs to be reordered once to ensure the orderliness of the section numbers in the section group. The section group division result is used as the basis for the segmentation of the combined number. After the section group division, the last field of each section group is extracted as the identification feature field. The combination is distinguished by whether the identification field is repeated. In this process, an independent index code value corresponding to each group of section numbers is formed. This code value is set as the segment identifier part in the combined sequence number code. For example, if the number sequence is T02, T03, T04, T06, it can be divided into two section groups: T02 to T04 and T06. The corresponding combined section identifiers are set as 0201 and 0202. Then, the combined section group number is used to generate an independent combined sequence number code segment, and finally, the independent combined sequence number is obtained.

[0054] The structure diagram code construction submodule adjusts the sub-category number based on the independent combination sequence number and the fastener main category code, sub-category code and sub-category number, and completes the field structure reorganization by corresponding with the combination sequence number. It also performs duplicate verification and number position verification to obtain the fastener segment sequence identifier code.

[0055] After obtaining the independent combination serial number, it is concatenated and reconstructed with the fastener main category code, sub-category code, and sub-category number. In this process, the first two digits of the main category code, the three digits of the sub-category code, and the three digits of the sub-category number need to be extracted first. For example, main category 01, sub-category 001, and sub-category 099 are combined into 01001099. Then, the difference between the last three digits of the independent combination serial number and the last three digits of the sub-category number needs to be determined. If the difference between the two fields is greater than 3, the sub-category number field needs to be adjusted by carrying over. The adjustment method is to correct the sub-category number field backward so that the difference between it and the combination serial number field does not exceed 3. At the same time, it is ensured that the adjusted number does not duplicate the existing drawing code. After completion, the fields are concatenated in sequence to construct a complete 8-digit process drawing code. The concatenation format is main category code + sub-category code + corrected sub-category code. Finally, the uniqueness verification table is searched to confirm that the drawing code does not have conflicts or redundancies, and the fastener segment sequence identifier code is obtained.

[0056] Table 1. Examples of Fastener Thermal Process Section Matching

[0057]

[0058]

[0059] As shown in Table 1, there are significant differences between the main category code and the thermal process segment number corresponding to different fastener categories. In the process segment extraction submodule, this data is used for field filtering and segment sequence generation. In the combined sequence number calculation submodule, the segment group division and combined code construction are based on this data. In the structure diagram code construction submodule, the main category, subcategory and combined fields are spliced ​​to generate an 8-digit process diagram code, forming a complete identification structure.

[0060] Please see Figure 3 The image and code parsing module includes:

[0061] The image acquisition submodule obtains the fastener segment sequence identification code, acquires the image corresponding to the identification area on the surface of the fastener entering the furnace, reads the image data stream and performs image grayscale conversion processing, performs tilt correction processing on the QR code image area, and obtains a structured image array.

[0062] After obtaining the fastener segment identification code, an image of the fastener surface code is acquired using an industrial camera or barcode scanner. During execution, the device must be aligned with the center of the code area and the shooting distance adjusted to ensure the code edges are clearly discernible. The image acquisition end then digitizes the original image signal and converts it into a pixel array matrix. Subsequently, the image is converted into a grayscale image to eliminate boundary recognition errors caused by color interference. When extracting the code area, a coordinate system matrix needs to be established for positioning. The code boundary is often determined by setting an image edge intensity threshold difference. A contrast ratio exceeding 70 units is considered a boundary area. For example, if the grayscale contrast ratio of image IMG001 is 75, it meets the boundary extraction requirements. After extraction, it is necessary to detect image distortion caused by tilt during shooting, combined with the sensor attitude information of the acquisition device. The tilt angle is corrected. When the tilt angle exceeds 3 degrees, a projection transformation is required to restore the front view structure. For example, if the tilt angle of IMG003 is 3.2°, this processing logic is triggered. In addition, during the correction process, it is also necessary to detect whether the QR code boundary box is closed. This is judged by detecting the symmetry of the four corner positioning modules of the QR code. If the symmetry ratio is not met, it is marked as "boundary recognition failure". For example, the failure of IMG003 and IMG005 in the boundary detection stage in Table 1 is due to symmetry error. After the boundary detection is successful, the image block division stage is entered. The QR code area is divided into several modules and the pixel grayscale difference of each module is detected. If the grayscale range difference in the pixel module exceeds 10 units, it is marked as a valid information module. The grayscale contrast is enhanced accordingly, and the pixel array is normalized again to finally obtain the structured image code array.

[0063] Table 2 Examples of QR code image acquisition

[0064] Image number Tilt angle (°) Grayscale contrast QR code boundary recognition successful IMG001 2.5 75 yes IMG002 1.8 82 yes IMG003 3.2 69 no IMG004 0.9 90 yes IMG005 4.0 65 no

[0065] As shown in Table 2, some images failed to extract the QR code region due to excessive tilt angle or insufficient contrast. In the acquisition step, tilt angle detection and grayscale difference judgment mechanism were introduced to ensure image region division, and finally a structured image code array was obtained.

[0066] The structure sequence number parsing submodule is based on the structured image array. It extracts the structured process code from the QR code, splits it into main category, subcategory, fine category and combination sequence number, and performs validity verification to determine whether there is code length abnormality or non-matching structure. It also performs field reconstruction operation to obtain the parsed structure sequence number value.

[0067] Based on a structured image array, the embedded structured process code information is extracted by scanning the QR code content row by row and column by column. This code uses an 8-bit structure field, where the first two bits are the main category code, the middle three bits are the sub-category code, and the last three bits are the sub-category and combination sequence number field. During image processing, the QR code element matrix structure is first identified. This structure is a 29×29 pixel array, where each element represents a logical bit unit. A grayscale threshold is used to classify each element as either "0" or "1". The threshold is typically set to 128 grayscale units; a grayscale value greater than this value is considered "1", and a value less than this value is considered "0". For example, if the grayscale value sequence of a row of elements is [130, 125, 132, 127], then its corresponding bit value is [1, 0]. Next, the image code content is read sequentially. Based on the starting position of the field, the main class field, such as "01", the subclass field, such as "005", and the combined field, such as "102", are extracted to form the structure sequence number 01005102. Then, the field structure is compared with the field length requirement for verification. If the length is not equal to 8 or a certain segment does not meet the character length requirement, an invalid mark operation is triggered. At the same time, the character encoding range of the field is verified. For example, the combined field must be numeric. If letters or special symbols appear, it is judged as an illegal format. In addition, the redundant bits set inside the QR code are compared. When the extracted field is inconsistent with the redundant verification field, the error bit needs to be repaired by reconstructing the logical bit stream. Finally, a valid 8-bit structure sequence number value is generated, and the parsed structure sequence number value is obtained.

[0068] The segment sequence statistics and verification submodule performs a matching query operation based on the combination sequence number in the parsed structure sequence number value, establishes an index column for each segment sequence number field in order, and completes the validity confirmation of the segment group based on the sequence continuity check and fluctuation judgment, and obtains the thermal process segment sequence index result;

[0069] After obtaining the combined sequence number information from the parsed structure sequence number value, the corresponding segment sequence index information is matched from the structure process database. In this process, the last two digits representing the segment group in the combined field must first be parsed. This field typically represents the sequence segment number in the heat treatment process. For example, the field "102" indicates that the segment sequence index contains sub-segments such as process segments 10, 11, and 12. The database is then searched to see if a process flow segment record with this sequence number exists. If the record exists, its process segment number set is extracted into a segment sequence field set. For example, the segment sequence field corresponding to combined segment 102 is [10, 11, 12, 13]. Subsequently, the sequence of this set is checked to determine whether the numbers are consecutive and whether there are any segment number jumps. If the segment number increment in the segment sequence field is not equal to 1, it is recorded as a discontinuous segment group. For example, if segment sequence [10, 11, 13] is missing segment 12, it is determined to be a skip segment group. Continue to count the interval values ​​between adjacent segment numbers and generate a segment sequence index structure. At the same time, count the mean, maximum interval value and standard fluctuation of this field set to determine whether the field is stable. When the maximum interval value is greater than 2, mark the segment sequence of this field as having too large a fluctuation and record the abnormal segment group. Regarding the average value range of the segment sequence, if the average value of the field is between 10 and 15, it is judged as a normal segment group. If it is lower than 10 or higher than 15, it is considered as deviating from the standard segment number range. Through the above screening process, the completeness of the segment sequence is finally screened and the index mapping result is established to obtain the thermal process segment sequence index result.

[0070] Please see Figure 4 The parameter instruction generation module includes:

[0071] The process parameter extraction submodule reads the process segment parameters corresponding to each segment number segment by segment from the segment sequence index result of the thermal process segment sequence, establishes a one-to-one correspondence between process segments and parameter values, and uses the following formula:

[0072]

[0073] The calculation obtains the segment sequence number parameter deviation judgment value, and generates a set of hot segment parameter deviation values, where Q i This represents the temperature deviation judgment value for segment i, in K and T. i Here is the target temperature value for segment i, in Kelvin. This is the average of the target temperature values ​​for all segments, in K and T. j This is the index parameter for the temperature value of the j-th segment, with an index range of j = 1 to n, and the unit is K, T. l T l+1 This represents the target temperature values ​​of adjacent segments l and l+1, in K, and n represents the total number of segments.

[0074] Based on the segment number set provided in the thermal process segment sequence index, the target temperature value and duration value corresponding to each segment number are sequentially read from the heat treatment parameter set. First, the segment number field "segment number" is extracted and used as a filtering criterion to locate the temperature and time fields in the parameter set. After calling the segment number, the fields "temperature value" and "duration value" are read from the parameter database, and a mapping relationship is established between the number and the parameter fields. For example, segment numbers 01, 02, and 03 correspond to temperature values ​​of 1123K, 1150K, and 1175K, respectively, and corresponding durations of 180s, 200s, and 210s, respectively, forming the preliminary segment parameter set [1123K, 180s], [1150K, 200s], and [1175K, 210s]. Subsequently, the average value of the temperature field set for that segment is calculated. To assess the deviation of each segment, the current segment T is then extracted. i Its value is then used in subsequent calculations, where the deviation index Q is included. i Calculate the temperature deviation value first, following the steps below. Multiply by the temperature value T of that segment. i After constructing the temperature variance term, the ratio to the square root of the mean square deviation of all segment temperatures yields a fractional term. The sum of the differences between adjacent terms in the temperature sequence is then added to form a complete deviation index. Each parameter in this calculation structure is in units of K. For example, when the total number of segments is 5, the corresponding temperature fields are shown in Table 5. If the selected segment is number 03, then T3 = 1175K. Substituting this into the equation, we get:

[0075]

[0076] After calculation, the deviation index Q3≈239.35K of segment 03 was obtained. This value indicates that the temperature of this segment deviates significantly from the average value of the segment and affects subsequent packaging. Finally, a set of thermal segment parameter deviation values ​​was generated.

[0077] Table 3 Target Temperature Sampling Table for Heat Treatment Section

[0078] Segment number Temperature value (K) 01 1123 02 1150 03 1175 04 1140 05 1135

[0079] As shown in Table 3, the temperature distribution in the five segments shows a non-linear trend. The value of segment 03 is more than 30K higher than the average. The calculation results are used for parameter anomaly identification and segment data filtering.

[0080] The parameter deviation judgment value is used to measure the degree of temperature anomaly of a certain heat treatment section in the entire process sequence. Its specific significance lies in the measurement of the relative distance between the target temperature value of the section and the overall temperature average, as well as the degree of response to temperature jump behavior in the section. The larger the value, the more significant the temperature deviation of the section is relative to the average level. At the same time, it may be at a jump node or abnormal section in the overall temperature change process of the sequence. Therefore, this parameter can be used as one of the important indicators for identifying the rationality of process parameters. It can reflect the temperature stability of a single section and also help to reveal the local abnormal section groups in the overall trend of the heat treatment sequence. This helps to screen out or reconstruct abnormal section parameters in the subsequent structure construction, thereby improving the continuity and consistency of the sequence parameter set.

[0081] The core logic of the formula can be divided into two parts: the first part is the fractional term, which aims to reflect the relative deviation between the current segment temperature value and the average value of the segment group. This deviation is achieved by considering the difference between the current segment temperature value and the average value. This represents the temperature deviation of the segment, and is then compared with its own temperature value T. i Multiplication amplifies the deviation values ​​according to their temperature range, reflecting the sensitivity of deviations in the high-temperature range. The denominator sums and takes the square root of the squared values ​​of the temperature deviations of all segments to form a standardized coefficient, making the deviation values ​​between different segments comparable, thus forming a normalized relative temperature volatility. The second part is the sum of the absolute values ​​of the differences between the temperature values ​​of all adjacent segments, ∑|T l -T l+1 This section describes the cumulative degree of temperature jump in the overall sequence and measures the overall temperature stability of the thermal sequence. Finally, by adding the two parts above, the intensity of temperature deviation in a single segment and the trend of segment fluctuation are comprehensively reflected, which is used to judge the rationality and the degree of fluctuation of the current segment in the overall process structure.

[0082] The instruction structure encapsulation submodule constructs a structured process parameter unit body based on the hot section parameter deviation value set, generates a unique segment code identifier field for each structure body, encapsulates all segment parameter units through a structure array, establishes a segment sequence structure table, and obtains the process parameter structure array;

[0083] Based on the parameter content of each segment in the set of hot segment parameter deviation values, encapsulated structure units are constructed from the filtered target temperature and duration values. First, the field content format is determined, the segment number is set to an 8-bit unsigned integer, the temperature field uses a 16-bit signed floating-point number, and the time field uses a 16-bit unsigned integer. Then, a unique identifier value is generated for each group of structure units, and all segment numbers are arranged in order and embedded into the structure array. In this structure array, each structure occupies a width of 64 bits. The structure is combined by calling the segment number sequence field and the corresponding parameter field. At the same time, it is checked whether there are duplicate segment number identifiers or empty segment parameters. If they exist, abnormal structures are marked and removed. For example, the structure formats of segment numbers 01 and 02 are [01, 1123, 180] and [02, 1150, 200], respectively. When constructing the structure array, they are merged in order of segment sequence, and a field sequence mapping matrix is ​​established for the subsequent instruction generation module to call the structure field information, and finally obtain the process parameter structure array.

[0084] The control sequence index submodule rearranges the sequence numbers of each segment structure and marks the index numbers according to the process parameter structure array, identifies and reconstructs non-contiguous segment numbers, constructs the mapping between segment order and control index, assigns sequence numbers to the sequence field according to the loading order, and establishes a control instruction structure set.

[0085] Based on the segment sequence table in the process parameter structure array, a sorting operation is performed on the segment structure numbers. First, the segment number field in the structure array is extracted, and the segment number sequence is generated by sorting the field values ​​from smallest to largest. Then, a control index sequence is generated, and the index number corresponding to each segment is assigned sequentially from 0 to n. For example, if the segment number is [01, 02, 03, 04, 05], the corresponding index is [0, 1, 2, 3, 4]. If there are non-contiguous numbers such as [01, 02, 04, 05], the missing segment 03 is detected and an index flag bit -1 is inserted to indicate the missing field. Then, a one-to-one mapping table between the segment sequence field and the control index is established. The field contains three items: segment number field, index field, and logical loading sequence number field. The structure data table is reordered according to the index field, and a data path mapping relationship from this structure set to the control system is established. During the structure field call process, the control system can access each segment parameter group according to the loading order, and finally, a control instruction structure set is established.

[0086] Please see Figure 5 The temperature zone drive judgment module includes:

[0087] The temperature acquisition submodule, based on the control instruction structure set, determines that the current process segment is in the execution state, acquires the real-time temperature value of the fastener surface, and records it as a temperature vector array according to the sampling time sequence. Each sampled value is assigned a corresponding timestamp identifier to obtain the real-time temperature record array.

[0088] Based on the control command structure set, the segment number field and loading order field of each structure are called. After clarifying that the current process segment is in the actual operation stage, the temperature value of the fastener on the inner surface of the segment is collected by the embedded temperature sensor located inside the process equipment. The read temperature values ​​are recorded in the order of actual sampling time to generate a data vector array. The sampling period is uniformly configured and set to 5 seconds at the beginning of equipment startup, that is, the temperature value is recorded once every 5 seconds. In typical process settings, the duration of a single heat treatment process is usually controlled between 180 seconds and 220 seconds. Taking segment 2 as an example, the duration is set to 200 seconds. According to the 5-second sampling period, a total of 40 sets of temperature records are collected. The data recording format adopts a two-dimensional structure with timestamps. Each data... Each item contains a segment number, timestamp, and real-time temperature value field. After completing temperature sampling for a full segment cycle, the collected results are categorized by segment number and written to the cached data pool. During this process, the sampled data needs to be validated to detect obvious jumps, abnormally low values, or duplicate data. Sampled items that exceed the physically feasible range (such as below 300K or above 1600K) are determined to be invalid points and are removed. The number of valid records retained is used as the basic indicator of the segment's collected data volume and is recorded in the sampling metadata table. The sampling array is subjected to three steps: anomaly removal, sampling point segmentation and marking, and duplicate detection. Only after ensuring the continuity of data within the segment can it be submitted to the comparison module for the next stage of processing, ultimately obtaining the real-time temperature record array.

[0089] Table 4 Temperature Sampling Settings for Process Sections

[0090] Segment number Temperature sampling period (seconds) Duration (seconds) Number of sampling points 1 5 180 36 2 5 200 40 3 5 220 44

[0091] As shown in Table 4, the sampling period is set to be the same under different segment numbers, and different durations correspond to different numbers of temperature sampling points. The number of sampling points will directly affect the accuracy of subsequent comparison and judgment.

[0092] The temperature zone comparison submodule is based on each sampled value in the real-time temperature record array and confirms the material type of the current segment according to the segment number of the structure. It then checks and determines the temperature zone tolerance zone, compares the difference between the target temperature range and the sampled value range, judges whether all temperature values ​​in the sampled data fall within the target range, groups and marks the judgment results and archives them, summarizes the comparison of all sampling points, and obtains the segment temperature deviation trend record.

[0093] Read the temperature sampling values ​​recorded in each segment of the real-time temperature recording array, and based on the structure segment number field corresponding to the fastener material type of the current process segment, consult the temperature control setting table to determine that the temperature control range for carbon steel is set to ±15℃, and for alloy steel to ±10℃. After obtaining the target temperature value field and the offset tolerance parameter corresponding to the material, generate the upper and lower limits respectively. Then, compare the difference between each sampled temperature value and the temperature range to determine whether it is within the tolerance band. If it meets the range between the upper and lower limits, it is marked as valid; otherwise, it is marked as deviating. Count the total number of sampled points marked as deviating within the segment. Taking segment number 2 as an example, the target temperature is set at 850℃, corresponding to a tolerance range of 835℃ to 865℃ for carbon steel. If 6 out of 40 samples are below 835℃ or above 865℃, the deviation ratio is 15%. Based on the deviation judgment, the fluctuation range of the temperature value within the segment is compared and evaluated. The temperature stability within the segment is identified by detecting the change range between consecutive sample values. If there is a continuous interval where the fluctuation exceeds the set difference threshold (e.g., 25℃), it is recorded as unstable segment behavior. The deviation ratio and the number of fluctuations are used to construct the basis for segment temperature control behavior identification, and finally obtain the segment temperature deviation trend record.

[0094] The action triggering submodule records the segment temperature deviation trend, converts the results of each segment's marker array into a unified status flag, and determines whether the current segment meets the normal process conditions. If the status is determined to be abnormal, it is updated to the abnormal handling mode, synchronously writes the response instruction set, and generates a process segment temperature zone response flag set.

[0095] The normality of a segment is determined based on the recorded temperature deviation trend. First, the proportion of deviation sampling points within the segment is read, combined with the fluctuation count statistics. If either exceeds the set standard, the segment is deemed not to meet process requirements. Here, the temperature deviation ratio threshold is set at 10%. This value is based on the thermal conductivity hysteresis of carbon steel and alloy steel within the temperature control range and the length of the stable temperature range accommodated by the segment duration. With the carbon steel quenching temperature range set at 850±15℃, a sampling period of 5 seconds, a segment duration of 200 seconds, and 40 sampling points, a 10% deviation ratio means a maximum of 4 sampling points are allowed to be outside the effective temperature range. This value can cover short-term anomalies caused by non-structural fluctuations such as equipment heating inertia, sensor response delay, and environmental disturbances, providing tolerance within the equipment response time range. This ensures that deviation warnings are only triggered when the thermal inertia tolerance limit is exceeded. Simultaneously, the upper limit of the fluctuation range is also considered. The value is set to 3 times. This value is based on the time resolution of recording temperature changes once every 5 seconds in the sampling array and the minimum time interval for identifying continuous change segments. That is, if the temperature change amplitude between more than 3 adjacent sampling points in a segment exceeds the set jump benchmark value (such as 25℃), it can be determined that the temperature control in the segment is unstable. Setting this value can cover continuous jump behavior of more than 15 seconds in most hot segments, serving as the basis for judging the dynamic disturbance trend. This value increases proportionally as the sampling interval shortens or the duration of the hot segment lengthens. If the deviation ratio in the segment exceeds 10% or the number of fluctuations exceeds 3 times, the segment is determined to be an abnormal segment, triggering the change of the abnormal flag bit in the segment control field, activating the control field in the segment structure to execute the response instruction writing operation, and then importing the segment number, status identifier and corresponding control instruction into the response sequence list to generate the response action identifier content of the current segment, completing the response processing flow of the current segment under abnormal temperature control, and finally generating the process segment temperature zone response flag set.

[0096] Please see Figure 6 The state-autonomous response module includes:

[0097] The offset statistics submodule divides the sampling points into segments according to the response status identifier records of each segment in the temperature zone response marker set of the process section. It determines a valid offset when three adjacent sampling intervals are all marked as exceeding the temperature. The sampling interval of each group is fixed at 2 seconds. Therefore, the three consecutive points span a total of 6 seconds of time window. It identifies all the sequence groups that meet the conditions segment by segment, counts the cumulative number of valid offsets for each segment, and stores the offset counts in correspondence with the segment sequence number to obtain the segment offset count distribution data.

[0098] Based on the segment response status field recorded in the process segment temperature zone response marker set, the sampling time sequence and temperature exceedance marker field content corresponding to each segment are extracted. A record group consisting of consecutive sampling points is extracted from the temperature data in chronological order, with each group of sampling points spaced 2 seconds apart. It is determined whether the temperature in three consecutive groups of sampling data is continuously higher than the upper limit of the tolerance band. If so, it is identified as a valid offset event. During this process, identified events must be marked and excluded from the original data to avoid duplicate counting of the same offset segment. After completing the offset event identification within the entire segment sequence, the number of offset events for each segment is counted and written into a statistical mapping table corresponding to the segment number. For example, segment number 2 corresponds to 6 offset events, representing 6 independent consecutive temperature exceedance records within the sampling period. This value, along with the segment duration and sampling density, constitutes the offset feature dimension, as shown in Table 5. Segment 1 has a sampling interval of 2 seconds and a total sampling time of 180 seconds, corresponding to 4 offset events. Segment 3 has 2 offset events, forming a phased trend reference data for the input basis of the next step's cooling response judgment. Finally, the segment offset number distribution data is obtained.

[0099] Table 5. Offset Statistics and Cooling Correlation Parameters

[0100] Segment number Sampling interval (seconds) Number of offset sequences Segment duration (seconds) 1 2 4 180 2 2 6 240 3 2 2 200

[0101] As shown in Table 5, different segment numbers exhibit differentiated offset sequence behavior under a unified sampling configuration. This statistical result is used to establish the input mapping relationship between segments and cooling response.

[0102] The cooling control submodule compares the segment offset number distribution data with the cooling delay threshold, and according to the process settings, it retrieves the response flag status and segment duration fields, confirms the current operating status, writes and updates those that meet the cooling trigger requirements, sets the cooling response flag to the active state, and obtains the segment cooling response status record.

[0103] Based on the distribution data of segment offset counts, a judgment operation is performed against the set benchmark value in the cooling control module. The segment number corresponding to the offset count is compared with the benchmark value. The benchmark value is set with reference to the relationship between the sampling interval and the cooling trigger duration. This relationship requires that the temperature exceedance duration reaches 30 seconds before cooling can be triggered. The sampling interval is 2 seconds, and a single offset is 3 consecutive points. Therefore, at least 5 offset sequences must occur to meet the 30-second over-temperature requirement. This judgment is performed based on the actual number of offset groups without numerical conversion to avoid judgment distortion caused by changes in offset density. During the judgment process, the response status flag in the segment structure field needs to be retrieved simultaneously. If the flag is in an abnormal state and the offset count reaches the threshold, the cooling response flag is triggered and written to the segment control field. In the example, the offset count of segment 2 is 6, which is greater than the threshold. Therefore, the cooling action flag is executed. Other segments that do not meet the conditions are skipped without processing. After completing the judgment of all segment offset responses, a summary array of cooling status is obtained, and finally, the segment cooling response status record is obtained.

[0104] The record generation submodule records the segment cooling response status, constructs a structured record unit in the order of segment number, combines all segment control information, and uniformly encodes and marks the content of each response status to complete the encapsulation and classification of control behavior and establish an integrated control record for fastener heat treatment.

[0105] Based on the segment cooling response status record, the control information stored in the structure fields of each segment is archived. First, the segment sequence number field is extracted, and then the response status field, offset count field, and cooling flag field are read in segment order. The contents of the three types of fields are combined according to the segment number and uniformly written into the control record item to generate an integrated control data structure corresponding to each segment. The record does not contain the sampling data itself, but only retains the structured status information for process review and historical tracking operations. At the same time, the generated record items are arranged according to the segment sequence number and merged into the overall segment sequence control record table. A status tag is added to the end of each record to distinguish between regular segments and cooling segments. After the record is completed, it is uniformly written into the segment auxiliary information item as the basic record for subsequent process comparison and process optimization. Finally, an integrated control record for fastener heat treatment is established.

[0106] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A digital control system for integrated heat treatment of fasteners, characterized by, The system comprises: The process sequence setting module acquires the fastener category and the corresponding hot process segment sequence number, sets an independent integer type combination sequence number, embeds the combination sequence number into the process graph code construction structured identification pattern, and obtains a fastener segment sequence identification code; The graph code analysis module collects the fastener graph code image and extracts the corresponding structured sequence number according to the fastener segment sequence identification code, counts the corresponding process segment combination index, and generates a hot process segment sequence index result; The parameter instruction generation module reads the corresponding process segment number, target temperature point and duration point according to the hot process segment sequence index result, forms a sequence of independent control logic, encapsulates it into a structure array form, and generates a control instruction structure set; The temperature zone driving judgment module collects the real-time temperature of the fastener in the process segment based on the control instruction structure set, marks whether the temperature is in the corresponding segment temperature zone tolerance band, judges whether the control action is triggered, and generates a process segment temperature zone response marker set; The state autonomous response module counts the temperature deviation times in each segment according to the process segment temperature zone response marker set, executes a cooling operation when the deviation times exceed a cooling delay threshold, and records the state to generate a fastener heat treatment integrated control record.

2. The integrated digital control system for heat treating fasteners of claim 1, wherein, The fastener segment sequence identification code comprises a process category label, a segment sequence integer code, and a structured graph code embedded index; the hot process segment sequence index result comprises a structured segment sequence mapping relationship, a segment sequence combination index value, and a process segment associated parameter index; the control instruction structure set comprises a segment sequence parameter structure array, a target temperature control parameter set, and a loading sequence logic index; the process segment temperature zone response marker set comprises a temperature interval judgment identifier, an out-of-tolerance response flag record, and a material temperature difference tolerance label; and the fastener heat treatment integrated control record comprises a process segment state marker table, a cooling trigger log, and temperature deviation statistical data.

3. The integrated digital control system for heat treating fasteners of claim 1, wherein, The process sequence setting module comprises: The process segment extraction submodule determines the fastener category, reads the corresponding hot process segment sequence number in the process database, sequentially matches the corresponding numbers of each segment, judges whether the hot process segment number matches the category, filters the sequence numbers of all corresponding hot process segments, and generates a hot process segment number sequence; The combination sequence operation submodule extracts the intermediate field information of each number according to the hot process segment number sequence, arranges and compares the numbers, confirms the distinguishable coding segment positions, classifies the numbers in combination with the clustering characteristics of the sequence numbers, and establishes an independent combination sequence number; The structured graph code construction submodule adjusts the fine classification number according to the independent combination sequence number and the fastener main category code, the subcategory code and the fine classification number, reorganizes the field structure corresponding to the combination sequence number, and performs repetitive verification and number position checking to obtain the fastener segment sequence identification code.

4. The integrated digital control system for heat treating fasteners of claim 1, wherein, The graph code analysis module comprises: The graph code image acquisition submodule acquires the fastener segment sequence identification code, collects the corresponding graph code image of the identification area on the surface of the fastener entering the furnace, reads the image data stream and performs image grayscale conversion processing, and performs inclination correction processing on the two-dimensional code graph code area to obtain a structured graph code image array; The structure serial number analysis submodule extracts a structured process code in a two-dimensional code based on the structured code image array, splits a main class, a sub-class, a fine class, and a combined serial number, and performs an effectiveness checking operation to determine whether there is an abnormal code length or a non-matching structure, and performs a field reconstruction operation to obtain an analysis structure serial number value; The segment sequence statistical checking submodule performs a matching query operation according to the combined serial number in the analysis structure serial number value, arranges indexes in sequence according to segment serial number fields, and completes segment group effectiveness confirmation according to sequence continuity and fluctuation judgment to obtain a thermal process segment sequence index result.

5. The integrated digital control system for heat treating fasteners of claim 1, wherein, The parameter instruction generation module includes: The process parameter extraction submodule reads process segment parameters corresponding to each segment serial number in sequence according to a segment sequence set in the thermal process segment sequence index result, establishes a one-to-one correspondence between a process segment and a parameter value, calculates a segment serial number parameter deviation judgment value, and generates a thermal segment parameter deviation value set; The instruction structure packaging submodule constructs a structured process parameter unit based on the thermal segment parameter deviation value set, generates a unique segment code identification field for each structure, encapsulates all segment parameter units through a structure array, establishes a segment sequence structure order table, and obtains a process parameter structure array; The control sequence index submodule reorders and indexes serial numbers of each segment structure according to the process parameter structure array, identifies and reconstructs discontinuous segment numbers, constructs a mapping between a segment sequence and a control index, assigns a serial number to a sequence field according to a loading order, and establishes a control instruction structure set.

6. The integrated digital control system for heat treating fasteners of claim 1, wherein, The temperature zone driving judgment module includes: The temperature acquisition submodule acquires a fastener surface real-time temperature value after determining that a current process segment is in an execution state based on the control instruction structure set, records the real-time temperature value as a temperature vector array in a sampling time sequence, assigns a corresponding time stamp identification to each sampling value, and obtains a real-time temperature record array; The temperature zone comparison submodule compares each sampling value in the real-time temperature record array, determines a material type of a current segment according to a structure segment serial number, consults a temperature zone tolerance band, compares a target temperature range with a sampling value interval, judges whether all temperature values in the sampling data fall within the target range interval, groups and archives the judgment results, summarizes comparison conditions of all sampling points, and obtains a segment temperature deviation trend record; The action triggering submodule converts all segment marker array results into state identification bits, judges whether a current segment meets normal process conditions, updates to an abnormal processing mode if the state is determined to be abnormal, synchronously writes a response instruction set, and generates a process segment temperature zone response marker set.

7. The integrated digital control system for heat treating fasteners of claim 1, wherein, The state autonomous response module includes: The offset statistical submodule performs segment division on sampling points in sequence according to response state identification records of each segment in the process segment temperature zone response marker set, counts the number of valid offsets of each segment, stores the number of offsets corresponding to the segment serial number, and obtains segment offset frequency distribution data. The cooling control submodule compares the segment offset number distribution data with a cooling delay threshold, searches for a response flag state and a segment duration field according to a process setting, confirms the current running state, writes and updates the cooling response state record, sets the cooling response flag to an active state, and acquires the segment cooling response state record; The record generation submodule constructs a structured record unit in sequence according to the segment number, combines all segment control information, uniformly encodes and marks the response state content, encapsulates and classifies the control behavior, and establishes a fastener heat treatment integrated control record.

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