Production process traceability method of hub type transmission device

Abstract

The invention relates to the technical field of intelligent manufacturing and block chains, in particular to a production process traceability method of a hub type transmission device, which comprises the following steps: acquiring three types of operation data and aggregating to generate a synchronous value, calculating a parameter rate to judge whether the parameter rate exceeds a limit and extract a sudden change section, comparing a trend with a threshold value and reconstructing into a clamping state node, and packaging the signature and broadcasting to generate a verification node, and analyzing the node to supplement a link to generate right confirmation data. According to the method, parameter synchronism is calculated and recognized through the offset rate, the linkage analysis capability among multi-dimensional data is improved, accurate recognition of a sudden change section is achieved through comparison of continuous period parameter variation difference and double threshold values, and abnormal fragments are effectively extracted and an independent structure is formed by combining trend consistency and pressure difference value judgment; a signature and broadcast mechanism ensures the consistency of node data, link comparison and breakpoint reconstruction maintain the integrity of a data link, and the anomaly recognition precision, the node credibility and the production data closed-loop management capability are enhanced.

Description

Technical Field

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

[0002] The field of intelligent manufacturing and blockchain technology includes a collection of technologies that achieve full life cycle management of products through intelligent equipment, digital processes and trusted data links. The core content of this technology field is to collect, standardize and store data from design, production, use and maintenance in the manufacturing process in a structured manner, and manage the manufacturing execution in real time through process control methods. The application of blockchain technology in this field is mainly reflected in the ability to store manufacturing data in an unalterable manner, record the flow of data on the chain, and trace responsibility. Overall, this field emphasizes that the source of each data in the entire manufacturing process is credible, the process is traceable, the nodes are controllable, and the links are clear. It is suitable for the full process traceability management of complex structural components and supports intelligent operation and decision-making at all stages of the equipment life cycle.

[0003] Among them, the production process traceability method of the hub transmission device refers to the collection of component processing information, assembly sequence data, process parameter setting items, operator execution records, equipment operation status data, quality inspection process information, etc. in the manufacturing process of the hub transmission device, and combined with key elements such as process number, timestamp, location information, batch code, etc., by building a data chain composed of production nodes, the entire production process is recorded, chained and encoded. This method uses a unique identification generation rule to bind the component data identity, executes link construction based on the parameter consistency judgment strategy of the node data, encapsulates and writes each node data 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 the intelligent rule setting to organize the segmented traceability path of the node structure on the chain, completing the data structuring, sequencing and chain storage of the manufacturing resume.

[0004] Although the existing technology has coverage of parameter collection during the execution process, it lacks a real-time judgment mechanism for the linkage behavior between multiple parameters, and fails to build a synchronization analysis path based on the offset relationship between parameters, which easily leads to a single-point performance of equipment status identification. In terms of abnormal identification, it still relies on the static threshold judgment mode, lacks the means to capture the trend changes in the process of continuous parameter changes, and cannot accurately define the abnormal development section. In terms of data structure, no independent identification and reorganization method is established for abnormal information, resulting in information mixing that is not conducive to focused processing during tracing. The lack of structural consistency verification rules in the node propagation process increases the trust risk of data transmission on the chain. In the face of data chain breakpoints, a link judgment mechanism that relies on time series and trend values ​​has not yet been formed, and the broken chain position cannot be effectively identified and supplemented, and there is a structural gap in the continuity of production data. For example, under high-frequency production conditions, once the clamping force data is interrupted, it will affect the reasonable interpretation of power fluctuations, thereby reducing the accuracy of abnormal warnings and the integrity of chain records, limiting the stable operation and traceability reliability of the overall process. Summary of the invention

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

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a production process traceability method of a hub transmission device, comprising the following steps: S1: Collect the running status data of the clamping electric mechanism, power output interface and rotor driver, bind the timestamp, calculate the maximum difference and offset rate by periodic aggregation, judge the synchronization of the three parameters by 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 the power value according to the synchronous value of the three parameters of the rotating component, compare with the fluctuation threshold to determine whether it exceeds the limit, identify the mutation section and extract the fixed time parameter data before and after, and generate the mutation 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 trend directions are consistent, extract the machining pressure extreme value difference 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 the time period and number identifier, bind the private key to complete the signature and broadcast it to the chain network, verify the structural consistency, and 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 to generate production process confirmation data.

[0007] 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 confirmation data includes the clamping force continuity chain, the power value continuity chain and the link reconstruction result.

[0008] As a further solution of the present invention, the specific steps of S1 are: S101: Collect the running status of the clamping electric mechanism, the power output interface and the rotor driver, extract the clamping force, the current value and the 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 the 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 synchronization value of the three parameters of the rotating component.

[0009] As a further solution of the present invention, the difference interval value calculation formula is specifically: ; in, Representative cycle Neidi The difference interval value of the class parameter, Representation cycle Neidi The maximum value of the class parameter, Representation cycle Neidi The minimum value of the class parameter, Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The median value of the class parameter.

[0010] As a further solution of the present invention, the specific steps of S2 are: 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, and a parameter change rate sequence is generated; S202: calling the parameter change rate sequence, comparing the clamping force with the clamping force fluctuation threshold, the power rate value with the power jump threshold, respectively, extracting the data position where the two rates exceed the limit at the same time in the same cycle, and obtaining the two-item exceeding limit interval; S203: According to the over-limit interval, the clamping force, current value and power value in a fixed time period before and after each mutation point are extracted, and the original time position range is marked to generate a mutation section parameter group.

[0011] As a further solution of the present invention, the data difference intensity calculation formula is specifically: ; in, Indicates Class parameters in cycles With cycle The data difference intensity between Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The sampling point Class parameter values, Representation cycle The corresponding The sampling point Class parameter values, Indicated in 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.

[0012] As a further solution of the present invention, the specific steps of S3 are: S301: Obtain the clamping force and power value sequence in the mutation section parameter group, calculate the difference and determine whether the trend direction signs are consistent, calculate the consistent proportion, and generate a trend consistency coefficient; S302: Calculate the difference between the maximum and minimum values ​​according to the processing pressure sequence in the mutation section parameter group, and compare it with the pressure jump threshold to obtain the processing pressure jump offset; 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.

[0013] As a further solution of the present invention, the calculation formula for the difference between the maximum and minimum values ​​is specifically: ; 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.

[0014] As a further solution of the present invention, 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: According to 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 data transmission is verified to generate a broadcast verification node value.

[0015] As a further solution of the present invention, 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 according to 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 confirmation data.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: 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 realize 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 ensure 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

[0017] 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.

[0018] Figure 1 It is a schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0020] 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 "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0021] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0022] 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.

[0023] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0024] See also Figure 1 , a production process traceability method for a hub transmission device, comprising the following steps: S1: Collect the operating status of the clamping electric 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 respectively, aggregate the three data in the same time period, and then calculate the offset rate of the maximum value, minimum value and change difference in the aggregated data. The degree of synchronization of the periodic parameters is classified and judged by the offset rate, and the synchronization value of the three parameters of the rotating component is generated; S2: Calculate the instantaneous rate of change of the parameter according to the difference in the amplitude of the power value and the clamping force in two consecutive cycles of the three-parameter synchronization value of the rotating component, and then compare it with the clamping force fluctuation threshold and the power jump threshold to determine whether it exceeds the two set reference value ranges in the continuous interval. If the double-term tolerance condition is met, locate the sudden change state section, mark the parameter data of the time period before and after the sudden change point as a whole, and generate a sudden change section parameter group; S3: Obtain the clamping force, current value and power value sequence 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 obtain the difference, and make 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 to form an independent data structure, and generate the clamping state node value; S4: According to 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. Then, 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; 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 in the time period, and 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 production process confirmation data.

[0025] 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 abnormal characteristics, current abnormal characteristics and power abnormal 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 confirmation data includes the clamping force continuity chain, power value continuity chain and link reconstruction results.

[0026] The specific steps of S1 are: S101: Collect the running status of the clamping electric mechanism, the power output interface and the rotor driver, extract the clamping force, the current value and the power value, bind the collection timestamp, construct a time series set of three types of parameters, and generate a three-parameter time series set; 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 pressure sensor is arranged at each end of the clamping arm of the clamping electric mechanism, and 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 a timestamp record. For example, the clamping force value read at t=1.2 seconds is 32.5 Newtons, and the system marks the data as [ 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 be 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 amperes, then the current power is 110.4 watts, also recorded as [1.2s:110.4W]. The rotor driver operation status acquisition reads the data frame through the Modbus communication interface of the drive control unit, extracts the operation identification bit, speed value and load torque value in 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, then the clamping force, current and power data collected at the current time point are retained, otherwise the group of data is discarded. To ensure the synchronization of the three data, 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 of which contains three values: timestamp, clamping force, current, and power, forming a three-parameter time series set with a complete structure and consistent time matching.

[0027] 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; The specific calculation formula for the difference interval value is: ; in, Representative cycle Neidi The difference interval value of the class parameter, Representation cycle Neidi The maximum value of the class parameter, Representation cycle Neidi The minimum value of the class parameter, Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi median value of class parameter; This formula is used to calculate the cycle Neidi The difference interval value of the class parameter. For example, during an industrial clamping action, 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. The parameters are collected in real time through the strain sensor arranged in the clamping mechanism, and enter the system after signal conditioning and AD conversion. The collected data is as follows: 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) Calculate the maximum and minimum values: ; ; Difference: ; Calculate the average: ; Calculate the median: Arrange the data in ascending order: 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 an even number, the average of the 5th and 6th is the median: ; Calculate the difference between the mean and the median: ; Multiply by the adjustment factor 0.5: ; The final calculated difference interval value: ; The result shows that in 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 the value exceeds the clamping force stability threshold of 1.5 Newtons, the clamping state of this period is marked as an unstable state.

[0028] 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 the offset rate proximity, and obtaining the synchronization value of the three parameters of the rotating component; The relative offset ratios of the three types of parameter fluctuation values ​​in each polymerization cycle are calculated respectively. The ratio calculation method is to perform a ratio operation on each fluctuation value and 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 group of ratio values ​​is judged, i.e., 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., It is considered that the three types of parameters in this cycle are 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 to be synchronized. In the above cycle, the maximum offset value is 12.5%, the minimum is 3.03%, and the difference between the two is 9.47%, which is less than the threshold. Therefore, this cycle is marked as a synchronous 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 in all cycles and outputs a Boolean flag sequence indicating whether each cycle is synchronized, such as [T1: synchronous, T2: synchronous, T3: asynchronous, T4: synchronous], and finally generates a state sequence of the degree of synchronization of the three parameters of the clamping force, current and power of the rotating component in each cycle.

[0029] The specific steps of S2 are: 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, and a parameter change rate sequence is generated; The specific calculation formula of data difference intensity is: ; in, Indicates Class parameters in cycles With cycle The data difference intensity between Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The sampling point Class parameter values, Representation cycle The corresponding The sampling point Class parameter values, Indicated in 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; 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 100 milliseconds, the cycle is set to 1 second, and each cycle contains 10 groups of sampling points. Take this as an example for analysis.

[0030] 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: ; 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; ; The absolute value of the difference between the two period averages is: ; Then the absolute value of the difference of each corresponding point in the period is calculated, which are: [|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, |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; 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; The mean absolute difference is: ; Substitute into the formula to calculate: ; The results show that in the cycle With cycle The average clamping force changes by 1.00 N, the average difference of the sampling points is 0.94 N, and the combined cycle difference intensity 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.

[0031] S202: calling the parameter change rate sequence, comparing the clamping force with the clamping force fluctuation threshold, the power rate value with the power jump threshold, respectively, extracting the data position where the two rates exceed the limit at the same time in the same cycle, and obtaining the two-item exceeding limit interval; 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 comparison and 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 condition 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 power jump threshold is set to 25 watts per second. 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 is not exceeded 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 numbers that meet the conditions of both items exceeding the limit at the same time, and stores them in the double-item exceeding limit interval list, such as marked as T5-T6, T9-T10, T14-T15, etc., and finally obtains the double-item exceeding limit interval.

[0032] 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, and marking the original time position range to generate a mutation section parameter group; The starting time of each section 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 needs. 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 section, for a total of 40 groups. When the actual time value corresponding to the starting time tn+1 of each overlimit cycle Tn-Tn+1 is 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 in the target time period by timestamp to ensure data continuity. If there is a data gap of more than 200 milliseconds in the target interval, the mutation segment data 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 to construct a mutation segment parameter group data structure, which is arranged in chronological order. The mutation segment parameter group in the example 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.

[0033] The specific steps of S3 are: S301: Obtain the clamping force and power value sequence in the mutation section parameter group, calculate the difference and determine whether the trend direction signs are consistent, calculate the consistent proportion, and generate the trend consistency coefficient; First, a sequence of continuous data points is extracted from each mutation segment in chronological order. Each group of data points contains a clamping force value and a power value. Then, starting from the second data point at 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, 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 is consistent, the system counts the number of consistent results of all trend comparisons in the mutation section, and divides it by the total number of comparable times to obtain the trend consistency ratio coefficient. For example, in a mutation section with a total of 10 continuous sampling points, a total of 9 groups of trend comparisons can be formed. If 7 groups of trends are consistent, the trend consistency coefficient is 7 divided by 9, which is 0.777, or 77.7%. In order to facilitate the determination of the trend consistency strength level, the system divides the trend consistency coefficient into judgment intervals, and sets the trend consistency coefficient to be greater than or equal to 0.85 as strong trend consistency, between 0.65 and 0.85 as medium consistency, and less than 0.65 as inconsistent trend. This setting is based on the analysis of 50 typical mutation data. 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, and finally a trend consistency coefficient is output for each mutation data segment.

[0034] S302: Calculate the difference between the maximum and minimum values ​​according to the processing pressure sequence in the mutation section parameter group, and compare it with the pressure jump threshold to obtain the processing pressure jump offset; 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.

[0035] Let's take an example to illustrate the calculation process: Assume that the processing pressure reading sequence in 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: ; Plugging these two values ​​into the formula to calculate the difference: ; The calculation results show that the range of processing pressure change in the investigated mutation section is 0.6MPa. 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.

[0036] 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; 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 mutation segment parameter group and assembles them into a clamping state node value in sequence. The node value contains three items of data: 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. 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.

[0037] 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; First, the parameter sequence of start time, end time, node number, clamping force, current and power is extracted from each group of clamping state node values, and formatted and filled according to the data fields specified by the on-chain transmission structure. The on-chain transmission structure requires that the fields contain five parts: node number, timestamp range, parameter type, parameter data list and data length. The system sets the node numbers to start from 001 in sequence. The timestamp range consists of the minimum time and maximum time in the clamping state 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 data, clamping force, current and power, 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 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 order to form an array structure. The system outputs the set of data packets required for the entire set of on-chain transmission structures, and finally generates the on-chain transmission structure.

[0038] S402: According to 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; 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.

[0039] 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 data transmission is verified, and a broadcast verification node value is generated; 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 meets 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, they are broadcast to other child nodes. After receiving, the child nodes repeat the verification process to confirm data consistency. For example, the signature data packet number 004 is received by the master node, and the decryption is completed. 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. After each broadcast verification process is completed, a broadcast verification node value is output, which eventually constitutes a set of nodes with broadcast completion marks for the entire chain network.

[0040] The specific steps of S5 are: 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 detect whether there is an interruption position at the same time, and obtain the interruption detection result; First, the corresponding data time period start and end timestamps and parameter content fields are extracted from each group of broadcast verification nodes, and arranged in chronological order as a set of continuous time series. Then the system calls the clamping force data link and the power value data link respectively, and compares the time tags of the two data links. The specific steps are as follows: the system compares the start timestamp of each clamping force data node with the timestamp in the power value data node to see if there is a corresponding item. If there are several continuous time periods in the clamping force time series, and there is a lack of corresponding items in the power data link within a certain time range, that is, there is a time period that cannot be matched, then the section is determined as an interruption position. For example, the continuous time period in the clamping force data link is 10.0s-14.0s, while the recorded time periods in the power value data link are 10.0s-12.6s and 12.8s-14. 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 the detection of stability, the system performs the above pairing operation on each node data link and then calculates the matching completeness ratio. For example, the total period of clamping force recording of a certain node is 40 groups of data, and the corresponding power values ​​are successfully matched with 38 groups, then 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.

[0041] S502: Analyze the continuity of the clamping force change rate in the time period before and after the node according to the interruption detection result, determine whether there is interruption and loss of data, and obtain a continuity judgment result; 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 first two groups. The judgment standard is: if the last two groups before the chain break are 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 changed suddenly. If it is judged to be discontinuous, there is a risk of trend interruption 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 changes to a decline after the chain break, the trend is inconsistent. Under the conditions of inconsistent trends and discontinuous rates, it is judged 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.

[0042] 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 confirmation data; Data completion is performed on all broken chain nodes that are judged to be "non-continuous". The completion 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. The system performs linear slope estimation and interpolation calculation without using any model algorithm. The missing time period is divided 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 estimated by the front and rear slopes and filled in with 35.9 Newtons and 36.1 Newtons respectively. The same method is used to complete the power value. The current data is proportionally mapped and completed according to the proportion of clamping force change. The system completes each Insert the corresponding timestamp of data binding and record the completion flag field, then merge the completion data segment into the original clamping state node value, and repackage 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 indicate in the structure whether the completion segment is included. If the completion segment is included, it is additionally marked "reconstructed: true". 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 embeds identification fields, time interval indexes, parameter group details, reconstruction marks and other information. The system merges all reconstructed node data packet sets into the final production process confirmation data.

[0043] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A production process traceability method for a hub transmission device, characterized in that: The following steps are involved: S1: Collect the running status data of the clamping electric mechanism, power output interface and rotor driver, bind the timestamp, calculate the maximum difference and offset rate by periodic aggregation, judge the synchronization of the three parameters by 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 the power value according to the synchronous value of the three parameters of the rotating component, compare with the fluctuation threshold to determine whether it exceeds the limit, identify the mutation section and extract the fixed time parameter data before and after, and generate the mutation 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 trend directions are consistent, extract the machining pressure extreme value difference 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 the time period and number identifier, bind the private key to complete the signature and broadcast it to the chain network, verify the structural consistency, and 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 to generate production process confirmation data.

2. The production process traceability method of a hub transmission device according to claim 1, characterized in that: 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 abnormal characteristics, the current abnormal characteristics and the power abnormal 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 confirmation data includes the clamping force continuity chain, the power value continuity chain and the link reconstruction result.

3. 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 running status of the clamping electric mechanism, the power output interface and the rotor driver, extract the clamping force, the current value and the 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 the 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 synchronization value of the three parameters of the rotating component.

4. The production process traceability method of a hub transmission device according to claim 3, 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, Representation cycle Neidi The maximum value of the class parameter, Representation cycle Neidi The minimum value of the class parameter, Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The median value of the class parameter.

5. The production process traceability method of a hub transmission device according to claim 3, characterized in that: The specific steps of S2 are: 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, and a parameter change rate sequence is generated; S202: calling the parameter change rate sequence, comparing the clamping force with the clamping force fluctuation threshold, the power rate value with the power jump threshold, respectively, extracting the data position where both rates exceed the limit at the same time in the same cycle, and obtaining the interval segment where both rates exceed the limit; S203: According to the over-limit interval, the clamping force, current value and power value in a fixed time period before and after each mutation point are extracted, and the original time position range is marked to generate a mutation section parameter group.

6. The method for tracing the production process of a hub transmission device according to claim 5, characterized in that: The data difference intensity calculation formula is specifically: ； in, Indicates Class parameters in cycles With cycle The data difference intensity between Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The average value of the class parameter, Representation cycle Neidi The sampling point Class parameter values, Representation cycle The corresponding The sampling point Class parameter values, Indicated in 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.

7. The method for tracing the production process of a hub transmission device according to claim 5, characterized in that: The specific steps of S3 are: S301: Obtain the clamping force and power value sequence in the mutation section parameter group, calculate the difference and determine whether the trend direction signs are consistent, calculate the consistent proportion, and generate a trend consistency coefficient; S302: Calculate the difference between the maximum and minimum values ​​according to the processing pressure sequence in the mutation section parameter group, and compare it with the pressure jump threshold to obtain the processing pressure jump offset; 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.

8. The production process traceability method of a hub transmission device according to claim 7, 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.

9. The method for tracing the production process of a hub transmission device according to claim 7, 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: According to 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 data transmission is verified to generate a broadcast verification node value.

10. The production process traceability method of a hub transmission device according to claim 9, 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 according to 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 confirmation data.

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