A production process traceability method for a hub transmission device

Abstract

The present invention relates to the field of intelligent manufacturing and blockchain technology, specifically a method for tracing the production process of a hub-type transmission device, comprising the following steps: collecting three types of operating data and aggregating them to generate synchronization values, calculating parameter rates to determine whether they exceed limits and extracting mutation segments, comparing trends and thresholds to reconstruct nodes into clamped state nodes, encapsulating signatures and broadcasting to generate verification nodes, parsing nodes to complete links and generate right confirmation data. In the present invention, parameter synchronization is identified through offset rate calculation, the linkage analysis capability between multi-dimensional data is improved, the continuous period parameter change difference is compared with the double threshold value to achieve accurate identification of mutation segments, combined with trend consistency and pressure difference judgment, effectively extracting abnormal fragments and forming independent structures, signature and broadcast mechanisms to ensure node data consistency, link comparison and breakpoint reconstruction to maintain data chain integrity, and enhance abnormal identification accuracy, node credibility and production data closed-loop management capabilities.

Description

Technical Field

[0001] The present invention relates to the fields of intelligent manufacturing and blockchain technology, and in particular to a method for tracing the production process of a hub-type transmission device. Background Art

[0002] The field of intelligent manufacturing and blockchain technology encompasses a collection of technologies that enable full product lifecycle management through intelligent equipment, digital processes, and trusted data links. The core of this technology area lies in the structured collection, standardized recording, and trusted storage of data from design, production, use, and maintenance stages of the manufacturing process, as well as the real-time management of manufacturing execution through process control. The application of blockchain technology in this area is primarily reflected in its ability to immutably store manufacturing data, record on-chain transactions, and trace responsibility. Overall, this area emphasizes the trusted source, traceable processes, controllable nodes, and clear links of every piece of data throughout the entire manufacturing process. It is suitable for full-process traceability management of complex structural components and supports intelligent operations and decision-making at all stages of the equipment lifecycle.

[0003] Among them, the production process traceability method of the hub transmission device refers to the item-by-item collection of component processing information, assembly sequence data, process parameter setting items, operator execution records, equipment operating status data, quality inspection process information, etc. in the manufacturing process of the hub transmission device, and combines key elements such as process number, timestamp, location information, batch code, etc., by building a data chain composed of production nodes to record, chain organize and encode the entire production process. This method uses unique identification generation rules to bind the component data identity, executes link construction based on the parameter consistency judgment strategy of the node data, encapsulates the data of each node into the block according to the characteristics of the blockchain structure, uses the summary field in the chain to summarize the key data, and combines with intelligent rule settings to organize the segmented traceability path of the node structure on the chain, completing the data structuring, sequencing and chain storage of the manufacturing history.

[0004] While existing technologies provide comprehensive parameter collection during execution, they lack a real-time mechanism for determining the interactions between multiple parameters and a synchronous analysis path based on inter-parameter offset relationships. This can lead to single-point identification of equipment status. For anomaly identification, they still rely on static thresholds, lacking the means to capture trends during continuous parameter fluctuations and failing to accurately delineate the anomaly development segments. Data structures lack independent identification and reorganization methods for anomaly information, resulting in information clutter and hindering focused processing during traceability. Node propagation lacks structural consistency verification rules, increasing trust risks during data transmission on the chain. In the event of data chain breakage, a link determination mechanism based on time series and trend values ​​has not yet been established, making it impossible to effectively identify and repair the broken link location, resulting in a structural gap in production data continuity. For example, during high-frequency production, interruptions in clamping force data can affect the interpretation of power fluctuations, reducing the accuracy of anomaly warnings and the integrity of chain records, limiting the stability and traceability of the overall process. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a production process traceability method for a hub-type transmission device.

[0006] To achieve the above-mentioned object, the present invention adopts the following technical solution: a method for tracing the production process of a hub-type transmission device, comprising the following steps:

[0007] S1: Collect the operating status data of the clamping motor mechanism, power output interface, and rotor driver, bind the timestamps, calculate the maximum difference and offset rate by periodic aggregation, determine the synchronization status of the three parameters based on the offset rate, and generate the synchronization value of the three parameters of the rotating component;

[0008] S2: Calculate the continuous periodic change rate of the clamping force and power value based on the synchronized values ​​of the three parameters of the rotating assembly, compare them with the fluctuation threshold to determine whether they exceed the limit, identify the sudden change section and extract the fixed time parameter data before and after to generate the sudden change section parameter group;

[0009] S3: Obtain the clamping force, current value, and power value in the mutation section parameter group, determine whether the clamping and power fluctuation trends are consistent, extract the extreme value difference of the processing pressure and compare it with the jump threshold, reconstruct the segment data into a separate node, and generate the clamping state node value;

[0010] S4: Encapsulate the clamped state node value according to its time period and number identifier, bind the private key and complete the signature, and broadcast it to the chain network. After verifying the structural consistency, generate a broadcast verification node value.

[0011] S5: Analyze the timestamp and clamping trend data in the broadcast verification node value to determine whether the original chain is broken. If there is a gap, fill the node link and generate production process confirmation data.

[0012] As a further solution of the present invention, the three-parameter synchronization value of the rotating component includes the clamping force offset rate, the current offset rate and the power offset rate, the mutation section parameter group includes the clamping force abnormality characteristics, the current abnormality characteristics and the power abnormality characteristics, the clamping state node value includes the abnormal time segment, the state identification number and the parameter reconstruction structure, the broadcast verification node value includes the timestamp chain sequence, the clamping force change trend and the signature verification mark, and the production process right confirmation data includes the clamping force continuity chain, the power value continuity chain and the link reconstruction result.

[0013] As a further solution of the present invention, the specific steps of S1 are:

[0014] S101: Collect the operating status of the clamping electric mechanism, power output interface and rotor driver, extract the clamping force, current value and power value, bind the collection timestamp, construct a time series set of three types of parameters, and generate a three-parameter time series set;

[0015] S102: calling the three-parameter time series set, aggregating the clamping force, current value and power value according to a set period, calculating the parameter difference interval value, and obtaining a parameter difference interval sequence;

[0016] S103: calling the parameter difference interval sequence, calculating the ratio of the three differences to the corresponding maximum values ​​according to the period, judging the degree of proximity of the offset rate, and obtaining the synchronous values ​​of the three parameters of the rotating component.

[0017] As a further solution of the present invention, the difference interval value calculation formula is specifically:

[0018] ;

[0019] in, Representative cycle Neidi The difference interval value of the class parameter, Represents a period Neidi The maximum value of the class parameter, Represents a period Neidi The minimum value of the class parameter, Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The median value of the class parameter.

[0020] As a further solution of the present invention, the specific steps of S2 are:

[0021] S201: Calculating a data difference intensity based on the clamping force and power values ​​in the three-parameter synchronization value of the rotating component, subtracting the previous cycle from the next cycle and dividing the result by the cycle duration, respectively calculating the clamping force change rate and the power change rate to generate a parameter change rate sequence;

[0022] S202: calling the parameter change rate sequence, comparing the clamping force with the clamping force fluctuation threshold, and the power rate value with the power jump threshold, respectively, extracting the data positions where both rates exceed the limit simultaneously within the same period, and obtaining the interval segment where both rates exceed the limit;

[0023] S203: extracting the clamping force, current value and power value in a fixed time period before and after each mutation point according to the over-limit interval, marking the original time position range, and generating a mutation section parameter group.

[0024] As a further solution of the present invention, the data difference intensity calculation formula is specifically:

[0025] ;

[0026] in, Indicates the Class parameters in cycles With cycle The data difference intensity between Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The sampling point Class parameter values, Represents a period The corresponding The sampling point Class parameter values, Indicates The absolute value of the difference between the data at the same position in two cycles is summed at each sampling point. Indicates the total number of sampling points in the current cycle.

[0027] As a further solution of the present invention, the specific steps of S3 are:

[0028] S301: Obtaining a sequence of clamping force and power values ​​in the mutation section parameter group, calculating the difference and determining whether the trend direction signs are consistent, calculating the consistency ratio, and generating a trend consistency coefficient;

[0029] S302: Calculate the difference between the maximum and minimum values ​​of the machining pressure sequence in the mutation section parameter group, and compare it with the pressure jump threshold to obtain a machining pressure jump offset;

[0030] S303: calling the trend consistency coefficient and the machining pressure jump offset to determine whether they both exceed the set reference value. If so, extracting the corresponding parameter data to generate the clamping state node value.

[0031] As a further solution of the present invention, the formula for calculating the difference between the maximum and minimum values ​​is specifically:

[0032] ; Calculate the pressure jump offset, compare it with the pressure jump threshold, and obtain the processing pressure jump offset;

[0033] in, Represents the difference between the maximum and minimum values ​​of the processing pressure sequence in the mutation section parameter group, and They represent the maximum and minimum values ​​of the pressure sequence in the mutation section respectively.

[0034] As a further solution of the present invention, the specific steps of S4 are:

[0035] S401: Obtain the time period and number identifier in the clamped state node value, construct a data packet that meets the requirements of the on-chain transmission structure, and encapsulate the data packet to generate an on-chain transmission structure;

[0036] S402: Based on the on-chain transmission structure, the local private key is called to sign the encapsulated data, generate a signed data packet, verify the accuracy of the data, and obtain a signed data packet;

[0037] S403: Based on the signature data packet, the signed node is synchronized to the chain network through the blockchain node broadcast mechanism, the consistency of the node structure and the signature content is verified, and the stability of the data transmission is verified to generate a broadcast verification node value.

[0038] As a further solution of the present invention, the specific steps of S5 are:

[0039] S501: Obtain the timestamp sequence and the clamping force trend value in the broadcast verification node value, compare the time periods of the clamping force data chain and the power value data chain one by one, and simultaneously detect whether there is an interruption position, and obtain an interruption detection result;

[0040] S502: Analyze the continuity of the clamping force change rate in the time period before and after the node based on the interruption detection result, determine whether there is interruption and loss of data, and obtain a continuity determination result;

[0041] S503: Based on the continuity judgment result, the broken node data is supplemented and the link structure is rebuilt to generate a complete production process data chain and obtain the production process right confirmation data.

[0042] Compared with the prior art, the advantages and positive effects of the present invention are:

[0043] In the present invention, the synchronization of identification parameters is identified through offset rate calculation, the linkage analysis capability between multi-dimensional data is improved, the difference in parameter changes in continuous cycles and the comparison of double thresholds are used to achieve accurate identification of mutation segments, and the trend consistency and pressure difference judgment are combined to effectively extract abnormal fragments and form independent structures. The signature and broadcast mechanism ensures the consistency of node data, and the link comparison and breakpoint reconstruction maintain the integrity of the data chain, thereby enhancing the accuracy of abnormal identification, node credibility and closed-loop management capabilities of production data. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 Schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0046] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0047] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0048] In the embodiments of the present invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same. The terms "of," "corresponding," and "corresponding" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same.

[0049] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0050] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0051] See also Figure 1 A method for tracing the production process of a hub transmission device comprises the following steps:

[0052] S1: Collect the operating status of the clamping motor mechanism, power output interface, and rotor driver in the hub transmission device, bind the current timestamp to the clamping force, current value, and power value, aggregate the three data items according to the same time period, and then calculate the offset rate of the maximum, minimum, and change difference in the aggregated data. The offset rate is used to classify and judge the degree of synchronization of the periodic parameters and generate the synchronization value of the three parameters of the rotating component;

[0053] S2: Based on the difference in the amplitude of the power value and the clamping force in two consecutive cycles of the three-parameter synchronous value of the rotating component, the instantaneous change rate of the parameter is calculated, and then compared with the clamping force fluctuation threshold and the power jump threshold to determine whether it exceeds the two set reference value ranges within the continuous interval. If the double-term tolerance condition is met, the sudden change state segment is located, and the parameter data of the time period before and after the sudden change point is marked as a whole to generate a sudden change segment parameter group;

[0054] S3: Obtain the clamping force, current value, and power value sequences in the mutation section parameter group, calculate the trend sign consistency between the clamping force fluctuation rate and the power change rate, then take the maximum and minimum values ​​in the processing pressure sequence and calculate the difference, and perform a single comparison with the processing pressure jump threshold. If both judgment conditions are met, select the time period data segment as the abnormal section, reorganize the parameters into an independent data structure, and generate the clamping state node value;

[0055] S4: Based on the time period and number identifier in the clamped state node value, it is encapsulated into an on-chain transmission structure and bound to the local private key for signature processing. Subsequently, the signature node is synchronized to the chain network node through the blockchain node broadcast mechanism, the consistency between the node structure and the signature content is identified, and the broadcast verification node value is generated;

[0056] S5: Obtain the timestamp sequence and clamping force trend value in the broadcast verification node value, and compare the clamping force data chain and the power value data chain in sequence to see if there is an interruption position in the time period. Then, determine whether it is continuous based on the rate of change of the clamping force before and after the node. Use the node data to fill in the broken link and rebuild the link structure to generate the production process confirmation data.

[0057] The three-parameter synchronization values ​​of the rotating component include the clamping force offset rate, current offset rate and power offset rate. The mutation section parameter group includes the clamping force abnormality characteristics, current abnormality characteristics and power abnormality characteristics. The clamping state node value includes the abnormal time segment, state identification number and parameter reconstruction structure. The broadcast verification node value includes the timestamp chain sequence, clamping force change trend and signature verification mark. The production process right confirmation data includes the clamping force continuity chain, power value continuity chain and link reconstruction results.

[0058] The specific steps of S1 are:

[0059] S101: Collect the operating status of the clamping electric mechanism, power output interface and rotor driver, extract the clamping force, current value and power value, bind the collection timestamp, construct a time series set of three types of parameters, and generate a three-parameter time series set;

[0060] First, the acquisition tasks are divided into three groups: clamping force acquisition, current acquisition and power acquisition. During the clamping force acquisition process, a tension and pressure sensor is arranged at each end of the clamping arm of the clamping electric mechanism. At the same time, a redundant sensor is arranged at the central symmetrical position of the clamping mechanism to monitor the force changes during the clamping process. Through the timer control unit with a sampling interval of 100 milliseconds, the feedback value of the clamping force sensor read each time is recorded as the current clamping force value, and the current reading time of the system is bound as the timestamp record. For example, the clamping force value read at t=1.2 seconds is 32.5 Newtons, and the system marks this data as [ 1.2s:32.5N] is stored in the cache. When collecting the current value, a Hall current sensor is connected in series to the DC input end of the main circuit of the clamping mechanism motor to read the current change during the working process of the clamping motor. The sampling frequency is set to the same as the clamping force. The current value is read every 100 milliseconds and the timestamp is recorded synchronously. For example, when t=1.2 seconds, the current is 2.3 amperes, which is recorded as [1.2s:2.3A]. The power value is collected based on the voltage and current values ​​read at the same time. The control system multiplies the two data to obtain the power value at the corresponding moment. For example, when t=1.2 seconds, the voltage is read as 48 volts, current is 2.3 amps, then the current power is 110.4 watts, also recorded as [1.2s: 110.4W]. The rotor drive operating status is collected by reading the data frame through the Modbus communication interface of the drive control unit. The operation identification bit, speed value and load torque value are extracted from the data frame as the basis for judging whether the current drive is in normal working state. If the operation identification bit value is "01", it means that the drive is running stably. The three data items of clamping force, current and power collected at the current time point are retained. Otherwise, the data group is discarded. To ensure the synchronization of the three data items, the system sets a timestamp. The error tolerance does not exceed 1 millisecond. If the time deviation of any data exceeds this threshold, the data set will be discarded. For example, if the clamping force recording time is 1.200 seconds, the current recording time is 1.201 seconds, and the power time is 1.199 seconds, the data synchronization is successful. If the current recording time is 1.205 seconds, the data set will not be used. Finally, in a clamping operation cycle lasting 20 seconds, if the sampling frequency is 10 times per second, a total of 200 sets of three-parameter data can be collected. Each set contains three values: timestamp, clamping force, current, and power, forming a three-parameter time series set with a complete structure and consistent time matching.

[0061] S102: calling a three-parameter time series set, aggregating the clamping force, current value, and power value according to a set period, calculating the parameter difference interval value, and obtaining a parameter difference interval sequence;

[0062] The specific calculation formula for the difference interval value is:

[0063] ;

[0064] in, Representative cycle Neidi The difference interval value of the class parameter, Represents a period Neidi The maximum value of the class parameter, Represents a period Neidi The minimum value of the class parameter, Represents a period Neidi The mean value of the class parameter, Represents a period Neidi median value of the class parameter;

[0065] This formula is used to calculate the cycle Neidi The difference interval value of the class parameter. For example, during an industrial clamping operation, the sampling frequency is set to 100 milliseconds and the sampling period is set to 1 second. The equipment collects a total of 10 sets of clamping force values ​​during this period. This parameter is collected in real time by the strain sensor arranged in the clamping mechanism, and then enters the system after signal conditioning and AD conversion. The collected data is as follows:

[0066] The sampling sequence is: 31.8, 32.2, 32.5, 32.0, 32.7, 32.9, 33.1, 32.6, 32.4, 33.0 (unit: cow)

[0067] Calculate the maximum and minimum values:

[0068] ;

[0069] ;

[0070] Difference:

[0071] ;

[0072] Calculate the average:

[0073] ;

[0074] Calculate the median:

[0075] Arrange the data in ascending order as follows: 31.8, 32.0, 32.2, 32.4, 32.5, 32.6, 32.7, 32.9, 33.0, 33.1. Since the number of data is even, the average of the 5th and 6th data points is the median:

[0076] ;

[0077] Calculate the difference between the mean and the median:

[0078] ;

[0079] Multiply by the adjustment factor 0.5:

[0080] ;

[0081] The final calculated difference interval value:

[0082] ;

[0083] The results show that within the current sampling period, the maximum and minimum fluctuations of the clamping force parameter are 1.3 Newtons, and its central trend deviation is 0.03 Newtons. After weighting, the final clamping force difference interval value is 1.315 Newtons. This value represents the degree of clamping force fluctuation and the fluctuation structure characteristics of this period. It is input as a data in the parameter difference interval sequence to the subsequent stage for offset rate and synchronization judgment. If this value exceeds the clamping force stability threshold of 1.5 Newtons, the clamping state of this period is marked as an unstable state.

[0084] S103: calling the parameter difference interval sequence, calculating the ratio of the three differences to the corresponding maximum value according to the period, judging the degree of offset rate proximity, and obtaining the synchronous value of the three parameters of the rotating component;

[0085] The relative offset ratios of the three types of parameter fluctuation values ​​in each polymerization cycle are calculated separately. The ratio calculation method is to perform a ratio operation on each fluctuation value with the maximum value of the same cycle. For example, in the 3rd second polymerization cycle, the clamping force fluctuation value is 1.0 Newton and the maximum value is 33.0 Newton. The offset ratio is 0.0303, i.e. 3.03%. The current fluctuation value is 0.3 amperes and the maximum current value is 2.4 amperes. The offset ratio is 0.125, i.e. 12.5%. The power fluctuation value is 7 watts and the maximum power is 112 watts. The offset ratio is 0.0625, i.e. 6.25%. The three types of ratio values ​​are [3.03%, 12.5%, 6.25%]. Then, the difference between the maximum and minimum values ​​in this set of ratio values ​​is judged, that is, the consistency of the parameter fluctuations in the cycle. The consistency is defined as the difference between the maximum and minimum offset ratios within the set synchronization threshold range, i.e. The three parameters of this cycle are considered synchronized. For example, the synchronization threshold is set to 10%, which is determined by analyzing the fluctuation ratio of 100 sets of periodic data. When the maximum difference between the three parameters does not exceed 10%, that is, 0.10, it is considered synchronized. In the above cycle, the maximum offset value is 12.5% ​​and the minimum is 3.03%. The difference between the two is 9.47%, which is less than the threshold. Therefore, this cycle is marked as a synchronized cycle. In another cycle, if the three offset values ​​are [2.5%, 2.8%, 13.5%] respectively, the maximum difference is 11.0%, which is greater than the threshold. This cycle is marked as asynchronous. This process continues throughout all cycles and outputs a Boolean flag sequence indicating whether each cycle is synchronized, such as [T1: synchronous, T2: synchronous, T3: asynchronous, T4: synchronous]. Finally, a state sequence of the synchronization degree of the three parameters of the rotating component clamping force, current and power in each cycle is generated.

[0086] The specific steps of S2 are:

[0087] S201: Based on the clamping force and power values ​​in the three-parameter synchronization value of the rotating component, the data difference strength is calculated, the clamping force change rate and the power change rate are calculated respectively by subtracting the previous cycle from the next cycle and dividing by the cycle length, and a parameter change rate sequence is generated;

[0088] The specific calculation formula for data difference intensity is:

[0089] ;

[0090] in, Indicates the Class parameters in cycles With cycle The data difference intensity between Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The sampling point Class parameter values, Represents a period The corresponding The sampling point Class parameter values, Indicates The absolute value of the difference between the data at the same position in two cycles is summed at each sampling point. Indicates the total number of sampling points in the current cycle;

[0091] The clamping force and power parameters are derived from the strain gauge force sensor and voltage and current acquisition module integrated in the electric clamping system. The sampling frequency is uniformly set to 100 milliseconds, the cycle is set to 1 second, and each cycle contains 10 sets of sampling points. Take the example for analysis.

[0092] cycle The sampling data source is the system database record. The 10 groups of clamping force data are: 31.5, 32.0, 32.2, 31.8, 32.4, 32.6, 32.5, 32.1, 32.3, 32.0. The average value is calculated by adding up all the data and dividing by the number of points:

[0093] ;

[0094] cycle The clamping force sampling data are: 32.6, 33.1, 32.9, 32.8, 33.0, 33.2, 33.4, 33.1, 33.3, 33.0;

[0095] ;

[0096] The absolute value of the difference between the two period averages is:

[0097] ;

[0098] Then the absolute value of the difference of each corresponding point in the period is calculated, which are:

[0099] [|32.6-31.5|=1.1,|33.1-32.0|=1.1,|32.9-32.2|=0.7,|32.8-31.8|=1.0,|33.0-32.4|=0.6,

[0100] |33.2-32.6|=0.6, |33.4-32.5|=0.9, |33.1-32.1|=1.0, |33.3-32.3|=1.0, |33.0-32.0|=1.0;

[0101] The sum of the absolute differences is: 1.1+1.1+0.7+1.0+0.6+0.6+0.9+1.0+1.0+1.0=9.4;

[0102] The mean absolute difference is:

[0103] ;

[0104] Substitute into the formula to calculate:

[0105] ;

[0106] The results show that in the period With cycle The average change in clamping force is 1.00 N, the average difference of the sampling points is 0.94 N, and the combined cycle difference strength is 1.94 N. This value is used to determine whether the clamping force change reaches the set threshold and serves as a prerequisite for rate judgment. If the value exceeds the set difference warning value of 2.0 N, the system will mark the cycle as an abnormal clamping fluctuation state and enter the synchronization offset screening.

[0107] S202: Calling the parameter change rate sequence, comparing the clamping force with the clamping force fluctuation threshold, and the power rate value with the power jump threshold, respectively, extracting the data positions where both rates exceed the limit simultaneously within the same period, and obtaining the interval segment where both rates exceed the limit;

[0108] The clamping force change rate and power change rate in each sequence item are compared with the pre-set clamping force fluctuation threshold and power jump threshold for amplitude judgment. The setting of the clamping force fluctuation threshold is based on the physical response speed allowed by the equipment structure. The maximum stable value of the clamping force change rate in 300 operations is 2.0 Newtons per second, so the clamping force rate threshold is set to 2.5 Newtons per second, and the power jump threshold is set to 25 watts per second based on the fluctuation limit value under the standard working conditions of power change. This setting is based on the actual power change amplitude and the interval between the instantaneous load capacity allowed by the equipment. When performing the judgment operation, the system converts the absolute value of each rate value and compares it with the respective thresholds. When the absolute value of the clamping force change rate is greater than 2.5 Newtons per second and the power change rate is greater than 2.5 Newtons per second, the system will automatically adjust the power consumption according to the actual power change amplitude and the power jump threshold. When the absolute value of is greater than 25 watts per second, the system determines that the cycle is a cycle in which both rates exceed the limit at the same time. For example, in the cycle T5-T6, the clamping force rate is 3.0 Newtons per second and the power rate is 28.7 watts per second, satisfying the condition that both items exceed the limit. The cycle is marked as an abnormal rate cycle. If the clamping force rate is 2.7 Newtons per second but the power rate is only 21.0 watts per second, it is regarded as a single abnormality because the power does not exceed the limit and is not recorded. The system continuously scans the entire parameter change rate sequence, repeats the above amplitude comparison process for each cycle item, and extracts the cycle segment number that meets the condition of both items exceeding the limit at the same time, and stores it in the list of double-item exceeding limit intervals, such as marked as T5-T6, T9-T10, T14-T15, etc., and finally obtains the double-item exceeding limit interval.

[0109] S203: extracting the clamping force, current value, and power value in a fixed time period before and after each mutation point based on the over-limit interval, marking the original time position range, and generating a mutation section parameter group;

[0110] The starting time of each segment is located, and around the time period of each mutation point, the original parameter data of fixed lengths are extracted forward and backward respectively as the segment data sets before and after the mutation. The length of the time period can be set according to the data refresh frequency and actual observation requirements. For example, the extraction range is set to 2 seconds before and after. If the sampling frequency is once every 100 milliseconds, 20 groups of data are extracted for each segment, for a total of 40 groups. When the starting time tn+1 of each over-limit cycle Tn-Tn+1 corresponds to an actual time value of 12.0 seconds, the system will extract the original data of clamping force, current and power from 10.0 seconds to 14.0 seconds, for a total of 120 items of data (40 groups for each of the three types of parameters). At the same time, the start and end times are marked as the original time position range before and after the mutation, that is, [10.0s, 14.0s]. During the extraction process, the system calls the three parameter The system retrieves the corresponding parameter value set within the target time period by timestamp to ensure data continuity. If there is a data gap of more than 200 milliseconds within the target interval, the data of the mutation segment will be invalidated and not included in the subsequent analysis. In addition, to facilitate subsequent review and comparison, the system retains the original time index and the corresponding clamping force, current and power values ​​in each mutation segment data set, and constructs a mutation segment parameter group data structure, which is arranged in chronological order. In the example, the mutation segment parameter group is: 10.0 seconds: [32.1N, 2.2A, 96W], 10.1 seconds: [32.4N, 2.3A, 98W], ..., 13.9 seconds: [35.7N, 2.6A, 118W], 14.0 seconds: [35.8N, 2.5A, 117W], thereby forming a mutation segment parameter group set corresponding to multiple mutation points.

[0111] The specific steps of S3 are:

[0112] S301: Obtain the clamping force and power value sequences in the mutation section parameter group, calculate the difference and determine whether the trend direction signs are consistent, calculate the consistency ratio, and generate the trend consistency coefficient;

[0113] First, a sequence of continuous data points is extracted from each mutation segment in chronological order. Each set of data points contains a clamping force value and a power value. Then, starting from the second data point from the beginning of the sequence, the difference between the current data point value and the previous data point value is calculated in sequence, and the difference is judged to be positive or negative to mark the trend direction of the current change. For example, if the clamping force values ​​are 32.0 N, 33.0 N, 34.2 N, and 33.8 N in a certain period of time, the first step difference is 1.0 N and the trend is positive, the second step difference is 1.2 N and the trend is positive, and the third step difference is −0.4 N and the trend is negative. Similarly, the same difference calculation is performed on the power sequence. For example, if the power values ​​are 90 W, 94 W, 98 W, and 96 W, the first step trend is positive, the second step is positive, and the third step is negative. The system compares each clamping force trend mark with the corresponding power trend mark. If the signs of the two are the same within the same time interval, it is recorded as a consistent trend; otherwise, it is recorded as an inconsistent trend. If the trend comparison results are consistent, the system counts the number of consistent results for all trend comparisons in the mutation segment and divides it by the total number of comparable results to obtain the trend consistency ratio coefficient. For example, in a mutation segment with a total of 10 consecutive sampling points, a total of 9 groups of trend comparisons can be formed. If 7 of them have consistent trends, the trend consistency coefficient is 7 divided by 9, which is 0.777, or 77.7%. To facilitate the determination of the trend consistency strength level, the system divides the trend consistency coefficient into judgment intervals. When the trend consistency coefficient is greater than or equal to 0.85, it is defined as strong trend consistency, between 0.65 and 0.85 as moderate consistency, and less than 0.65 as inconsistent trend. This setting is based on the analysis of 50 typical mutation data segments. The average trend consistency ratio of clamping force and power under the same control action is 0.79. Therefore, 0.65 is selected as the lower limit of consistency judgment. Finally, a trend consistency coefficient is output for each mutation data segment.

[0114] S302: Calculate the difference between the maximum and minimum values ​​of the machining pressure sequence in the mutation section parameter group, and compare it with the pressure jump threshold to obtain the machining pressure jump offset;

[0115] The formula for calculating the difference between the maximum and minimum values ​​is:

[0116] ; Calculate the pressure jump offset, compare it with the pressure jump threshold, and obtain the processing pressure jump offset;

[0117] in, Represents the difference between the maximum and minimum values ​​of the processing pressure sequence in the mutation section parameter group, and They represent the maximum and minimum values ​​of the pressure sequence in the mutation section respectively.

[0118] To illustrate the calculation process, let's assume that the sequence of processing pressure readings within a specific mutation section is: 2.3MPa, 2.8MPa, 2.5MPa, 2.9MPa, 2.4MPa. First, find the maximum and minimum values ​​of this set of data:

[0119] ;

[0120] Substitute these two values ​​into the formula to calculate the difference:

[0121] ;

[0122] The calculation results show that the processing pressure varies by 0.6 MPa within the mutation section under consideration. This difference will be compared with the set pressure jump threshold to determine whether the mutation is within the acceptable range or whether it triggers any concerns.

[0123] S303: calling the trend consistency coefficient and the processing pressure jump offset to determine whether they both exceed the set reference value. If they do, extracting the corresponding parameter data to generate the clamping state node value;

[0124] The two indicators corresponding to each mutation data segment are judged to determine whether the trend consistency coefficient and the pressure jump offset exceed their respective set reference values. The judgment rule is that the trend consistency coefficient must be greater than or equal to 0.85, and the pressure jump offset must be greater than 0.10 MPa. When the two conditions are met, the mutation data segment will be judged as an abnormal clamping state node. The system then extracts all the original data from the parameter group of the mutation segment and assembles them into a clamping state node value in sequence. The node value contains three data items: clamping force, current, and power, and their timestamp range. In the example, the trend consistency coefficient of a mutation segment is 0.89, and the pressure jump offset is 0.12 MPa, both items exceed the benchmark value, so this section is confirmed as an abnormal clamping state node, and the corresponding extracted parameter data are as follows: time from 12.0 seconds to 14.0 seconds, the clamping force sequence is [32.0N, 33.0N, 34.5N,…], the current is [2.2A, 2.3A, 2.4A,…], the power is [92W, 95W, 98W,…], and the total number of data groups is 20 groups. The system defines it as a complete node identification item and stores it in the clamping state node value set. Finally, multiple node records that meet the conditions are formed during the entire monitoring period, and each node record is associated with the trend consistency coefficient and the jump offset.

[0125] The specific steps of S4 are:

[0126] S401: Obtain the time period and number identifier in the clamped state node value, construct a data packet that meets the requirements of the on-chain transmission structure, and encapsulate the data packet to generate an on-chain transmission structure;

[0127] First, the parameter sequence of start time, end time, node number, clamping force, current and power is extracted from each group of clamping status node values, and formatted and filled according to the data fields specified by the on-chain transmission structure. The on-chain transmission structure requires the fields to contain five parts: node number, timestamp range, parameter type, parameter data list and data length. The system sets the node number to start from 001 in sequence. The timestamp range is composed of the minimum time and maximum time in the clamping status node value. For example, if a node number is 004 and the time range is 12.0 seconds to 14.0 seconds, the field is "12.0s-14.0s". Then, the three types of clamping force, current and power data are assembled into array structures respectively. Each type of array contains numerical data sampled at intervals of 100 milliseconds. For example, the clamping force array is [32.1, 32.4, 33.0, 33.5, ...] with a total of 20 items. The system sets the length of each type of array to [32.1, 32.4, 33.0, 33.5, ...]. The degree is recorded as the data length field, and the parameter type is marked as "F" for clamping force, "I" for current, and "P" for power. A multi-layer nested data structure field is constructed for encapsulation processing to ensure that the data packet meets the on-chain transmission structure standard in terms of length, format, and structure. The encapsulation structure is organized in JSON or byte stream. For example, a complete encapsulation structure is as follows: {"id":"004","time_range":"12.0–14.0","F":[32.1,…],"I":[2.3,…],"P":[96,…],"len":{"F":20,"I":20,"P":20}}. This structure provides formatted data units for subsequent on-chain transmission. Multiple node data are encapsulated in sequence according to the numbering sequence to form an array structure. The system outputs the set of data packets required for the entire on-chain transmission structure, and finally generates the on-chain transmission structure.

[0128] S402: Based on the on-chain transmission structure, the local private key is called to sign the encapsulated data, generate a signed data packet, verify the accuracy of the data, and obtain a signed data packet;

[0129] First, the private key file in the local security module is called. The private key is stored in the hardware encryption module or loaded in the form of key management service. It is not transmitted in plain text outside the data packet. The system extracts the unique summary fingerprint value of the encapsulated data packet through data summary operation. The summary value is usually processed using the SHA series function. For example, the data packet content is the clamping parameter data and time range of node 004. The summary content is generated as a set of 64-bit hash values. The local private key is then used to perform asymmetric encryption operations on the summary content to form a signature value with a fixed byte length. The signature value is attached to the end of the original data packet as an additional field to form a signature data packet structure. For example, the additional field at the end of the original data packet is "sign": "2f4a6c...c7f2". When the system verifies the signature, it will calculate the summary of the original data content in the same way, and use the corresponding public key to decrypt the signature value, and compare the decrypted summary value to see if it is consistent with the locally calculated summary. If they are consistent, it means that the data has not been tampered with. If they are inconsistent, the data packet is an illegal data packet and is rejected for synchronization. To enhance the stability of signature verification, the system performs byte-level splicing on all fields of the signed data packet and calculates the check length, and then compares it with the original encapsulation length field to ensure that the data structure is not damaged or omitted. For example, the encapsulation length is 620 bytes, and the total length after signature processing is 684 bytes. The system detects and records the signature block length as 64 bytes, verifies the data integrity, and includes it in the valid signature data packet set, and finally generates a signature data packet.

[0130] S403: Based on the signature data packet, the signed node is synchronized to the chain network through the blockchain node broadcast mechanism, the consistency of the node structure and the signature content is verified, the stability of the data transmission is verified, and the broadcast verification node value is generated;

[0131] The blockchain node interface module is called to broadcast the signed data packet through the chain network communication protocol. The system first confirms the current number of active nodes in the chain network and the reachability of the broadcast path. If the current number of active nodes is less than the set threshold of 3, the broadcast is suspended and the current time and number of nodes are recorded. If the node broadcast conditions are met, the system submits the signed data packet to the master node in the form of a transaction request. After the master node completes the reception, it verifies the integrity of the data packet structure. The verification content includes whether the time period label conforms to the specification, whether the data field is missing, whether the signature field exists, and whether the decrypted summary matches the original data summary content. After all fields are verified, it is broadcast to other child nodes. After receiving, the child node repeats the verification process to confirm the data consistency. For example, the signature data packet number 004 is received by the master node, and the decrypted data packet number 004 is received by the master node. After the encrypted signature field is matched successfully, it is then distributed to the remaining 8 nodes through the P2P network. Each node returns a broadcast response mark "ACK" after receiving it. The system counts the number of successful broadcasts and compares it with the total number of nodes. The broadcast response success rate is set to be no less than 80% to determine that the node broadcast is stable. For example, 7 out of 8 nodes return confirmation, and the success rate is 87.5%, which meets the threshold condition. If the success rate is lower than 80%, it is recorded as a broadcast failure and the data packet is marked for retransmission. During the broadcast process, the system writes the node number, reception time, original data length and signature consistency mark of all successful broadcasts and consistency verifications into the broadcast verification structure. Each time a broadcast verification process is completed, a broadcast verification node value is output, which eventually constitutes the full-chain network broadcast completion mark node set.

[0132] The specific steps of S5 are:

[0133] S501: Obtain the timestamp sequence and clamping force trend value in the broadcast verification node value, compare the time periods of the clamping force data chain and the power value data chain one by one, and simultaneously detect whether there is an interruption position, and obtain the interruption detection result;

[0134] First, the corresponding data time period start and end timestamps and parameter content fields are extracted from each set of broadcast verification nodes and arranged in chronological order to form a continuous time series. The system then calls the clamping force data link and the power value data link, comparing the time tags of the two data links. Specifically, the system compares the start timestamp of each clamping force data node with the timestamp of the power value data node to see if there is a corresponding item. If there are several consecutive time periods in the clamping force time series, but no corresponding items within a certain time range in the power data link, that is, there is an unmatched time period, then this section is determined to be a discontinuity. For example, the continuous time period in the clamping force data link is 10.0s–14.0s, while the time periods recorded in the power value data link are 10.0s–12.6s and 12.8s–14.0s. 0s, and the middle 12.6s–12.8s is missing, then the system marks the 12.6–12.8 second interval as the interruption position, and the system sets the time interruption judgment threshold to 200 milliseconds. This value is statistically set based on the data sampling frequency (every 100 milliseconds) and the double sampling interval error. If the time exceeds two consecutive sampling times, that is, 200 milliseconds, it is judged as an interruption. If the time difference is less than or equal to 100 milliseconds, it is classified as a normal sampling delay. To facilitate detection stability, the system performs the above pairing operation on each node data link and calculates the matching completeness ratio. For example, if the total time period of the clamping force record of a certain node is 40 groups of data, and the corresponding power values ​​are successfully matched with 38 groups, the matching degree is 95%. The system records the matching completeness and outputs the start and end time of each interruption segment, the affected data segment number and the number of breakpoints, and finally obtains the interruption detection result.

[0135] S502: Analyze the continuity of the clamping force change rate in the time period before and after the node based on the interruption detection result, determine whether there is interruption and loss of data, and obtain a continuity judgment result;

[0136] First, the clamping force data points within two seconds before and after the chain break are extracted and arranged in chronological order to form a clamping force change sequence. Then, the clamping force difference between two consecutive sampling points is calculated and divided by the time interval to obtain the clamping force change rate. For example, the data points before the chain break are 34.1 N at 12.2 seconds, 34.8 N at 12.3 seconds, 35.4 N at 12.4 seconds, and 36.0 N at 12.5 seconds, with change rates of 0.7, 0.6, and 0.6 N per second, respectively. The data after the chain break are 36.2 N at 12.8 seconds, 36.8 N at 12.9 seconds, and 37.5 N at 13.0 seconds, with change rates of 0.6 and 0.7 N per second, respectively. The system compares the continuity of the last two groups of rates before and after the chain break with the initial two groups. The judgment standard is: if the last two groups before the chain break are 34.1 N, 34.8 N, 35.4 N, and 36.0 N, respectively. If the difference between one group of rates and the first group of rates after the chain break is within 0.5 Newtons per second, the rate is considered to be continuous, otherwise it is a rate interruption. The system performs the same process for each broken chain segment and records the continuity judgment mark as "yes" or "no". If it is judged to be continuous, it means that although the data is missing during the interruption period, the overall trend has not undergone a sudden change. If it is judged to be discontinuous, there is a risk of trend breakage in this segment. The system also calculates whether the sign of the clamping force change trend remains consistent before and after the chain break. For example, if it continues to rise before the chain break and suddenly falls after the chain break, the trend is inconsistent. Under the conditions of inconsistent trends and discontinuous rates, it is determined that there is a structural interruption in the data. The system records the change rate difference, trend direction difference and final continuity judgment result corresponding to each broken chain segment, and finally obtains the continuity judgment result.

[0137] S503: Based on the continuity judgment result, the broken node data is supplemented and the link structure is rebuilt to generate a complete production process data chain and obtain the production process ownership confirmation data;

[0138] Data filling operation is performed on all broken chain nodes that are judged as "non-continuous". The filling method adopts the neighboring data extrapolation strategy. The specific process is: call the last three clamping force data before the chain break and the first three clamping force data after the chain break to perform numerical trend fitting. Without using any model algorithm, the system performs linear slope estimation and interpolation calculation, and divides the missing time period into several time points at intervals of 100 milliseconds. For example, the broken chain segment is 12.6 seconds to 12.8 seconds, a total of 200 milliseconds. Two groups of data points are inserted in the middle, 12.7 seconds and 12.8 seconds respectively. The corresponding clamping force values ​​are filled in with 35.9 Newtons and 36.1 Newtons respectively after estimating the front and back slopes. The same method is used for power value filling. The current data is proportionally mapped and filled according to the clamping force change ratio. The system fills in each Insert the corresponding timestamp of the data binding and record the completion flag field, then merge the completion data segment into the original clamping state node value, and re-encapsulate it into a new node data packet structure according to the original structure. The reconstructed data chain needs to re-check the time sequence, data length and field integrity. All node data are numbered in chronological order and indicated in the structure whether the completion segment is included. If the completion segment is included, an additional mark "reconstructed: true" is added. Finally, a data chain set with a complete continuous time range and no interruption segments is output to form a complete production process data chain. The data chain structure has embedded identification fields, time interval indexes, parameter group details, reconstruction flags and other information. The system merges all reconstructed node data packet sets into the final production process right confirmation data.

[0139] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for tracing the production process of a hub transmission device, characterized in that: The following steps are involved: S1: Collect the operating status data of the clamping motor mechanism, power output interface, and rotor driver, bind the timestamps, calculate the maximum difference and offset rate by periodic aggregation, determine the synchronization status of the three parameters based on the offset rate, and generate the synchronization value of the three parameters of the rotating component; S2: Calculate the continuous periodic change rate of the clamping force and power value based on the synchronized values ​​of the three parameters of the rotating assembly, compare them with the fluctuation threshold to determine whether they exceed the limit, identify the sudden change section and extract the fixed time parameter data before and after to generate the sudden change section parameter group; S3: Obtain the clamping force, current value, and power value in the mutation section parameter group, determine whether the clamping and power fluctuation trends are consistent, extract the extreme value difference of the processing pressure and compare it with the jump threshold, reconstruct the segment data into a separate node, and generate the clamping state node value; S4: Encapsulate the clamped state node value according to its time period and number identifier, bind the private key and complete the signature, and broadcast it to the chain network. After verifying the structural consistency, generate a broadcast verification node value. S5: Analyze the timestamp and clamping trend data in the broadcast verification node value to determine whether the original chain is broken. If there is a gap, fill the node link and generate production process confirmation data; The three-parameter synchronization value of the rotating component includes the clamping force offset rate, the current offset rate and the power offset rate; the mutation section parameter group includes the clamping force abnormality characteristics, the current abnormality characteristics and the power abnormality characteristics; the clamping state node value includes the abnormal time segment, the state identification number and the parameter reconstruction structure; the broadcast verification node value includes the timestamp chain sequence, the clamping force change trend and the signature verification mark; the production process right confirmation data includes the clamping force continuity chain, the power value continuity chain and the link reconstruction result.

2. The production process traceability method of a hub transmission device according to claim 1, characterized in that: The specific steps of S1 are: S101: Collect the operating status of the clamping electric mechanism, power output interface and rotor driver, extract the clamping force, current value and power value, bind the collection timestamp, construct a time series set of three types of parameters, and generate a three-parameter time series set; S102: calling the three-parameter time series set, aggregating the clamping force, current value and power value according to a set period, calculating the parameter difference interval value, and obtaining a parameter difference interval sequence; S103: calling the parameter difference interval sequence, calculating the ratio of the three differences to the corresponding maximum values ​​according to the period, judging the degree of proximity of the offset rate, and obtaining the synchronous values ​​of the three parameters of the rotating component.

3. The production process traceability method of a hub transmission device according to claim 2, characterized in that: The calculation formula of the difference interval value is specifically: ； in, Representative cycle Neidi The difference interval value of the class parameter, Represents a period Neidi The maximum value of the class parameter, Represents a period Neidi The minimum value of the class parameter, Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The median value of the class parameter.

4. The method for tracing the production process of a hub transmission according to claim 2, characterized in that: The specific steps of S2 are: S201: Calculating a data difference intensity based on the clamping force and power values ​​in the three-parameter synchronization value of the rotating component, subtracting the previous cycle from the next cycle and dividing the result by the cycle duration, respectively calculating the clamping force change rate and the power change rate to generate a parameter change rate sequence; S202: calling the parameter change rate sequence, comparing the clamping force with the clamping force fluctuation threshold, and the power rate value with the power jump threshold, respectively, extracting the data positions where both rates exceed the limit simultaneously within the same period, and obtaining the interval segment where both rates exceed the limit; S203: extracting the clamping force, current value and power value in a fixed time period before and after each mutation point according to the over-limit interval, marking the original time position range, and generating a mutation section parameter group.

5. The production process traceability method of a hub transmission device according to claim 4, characterized in that: The data difference intensity calculation formula is specifically: ； in, Indicates the Class parameters in cycles With cycle The data difference intensity between Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The mean value of the class parameter, Represents a period Neidi The sampling point Class parameter values, Represents a period The corresponding The sampling point Class parameter values, Indicates The absolute value of the difference between the data at the same position in two cycles is summed at each sampling point. Indicates the total number of sampling points in the current cycle.

6. The method for tracing the production process of a hub transmission device according to claim 4, characterized in that: The specific steps of S3 are: S301: Obtaining a sequence of clamping force and power values ​​in the mutation section parameter group, calculating the difference and determining whether the trend direction signs are consistent, calculating the consistency ratio, and generating a trend consistency coefficient; S302: Calculate the difference between the maximum and minimum values ​​of the machining pressure sequence in the mutation section parameter group, and compare it with the pressure jump threshold to obtain a machining pressure jump offset; S303: calling the trend consistency coefficient and the machining pressure jump offset to determine whether they both exceed the set reference value. If so, extracting the corresponding parameter data to generate the clamping state node value.

7. The method for tracing the production process of a hub transmission according to claim 6, characterized in that: The specific calculation formula for the difference between the maximum and minimum values ​​is: ; Calculate the pressure jump offset, compare it with the pressure jump threshold, and obtain the processing pressure jump offset; in, Represents the difference between the maximum and minimum values ​​of the processing pressure sequence in the mutation section parameter group, and They represent the maximum and minimum values ​​of the pressure sequence in the mutation section respectively.

8. The method for tracing the production process of a hub transmission device according to claim 6, characterized in that: The specific steps of S4 are: S401: Obtain the time period and number identifier in the clamped state node value, construct a data packet that meets the requirements of the on-chain transmission structure, and encapsulate the data packet to generate an on-chain transmission structure; S402: Based on the on-chain transmission structure, the local private key is called to sign the encapsulated data, generate a signed data packet, verify the accuracy of the data, and obtain a signed data packet; S403: Based on the signature data packet, the signed node is synchronized to the chain network through the blockchain node broadcast mechanism, the consistency of the node structure and the signature content is verified, and the stability of the data transmission is verified to generate a broadcast verification node value.

9. The method for tracing the production process of a hub transmission device according to claim 8, characterized in that: The specific steps of S5 are: S501: Obtain the timestamp sequence and the clamping force trend value in the broadcast verification node value, compare the time periods of the clamping force data chain and the power value data chain one by one, and simultaneously detect whether there is an interruption position, and obtain an interruption detection result; S502: Analyze the continuity of the clamping force change rate in the time period before and after the node based on the interruption detection result, determine whether there is interruption and loss of data, and obtain a continuity determination result; S503: Based on the continuity judgment result, the broken node data is supplemented and the link structure is rebuilt to generate a complete production process data chain and obtain the production process right confirmation data.

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