A method for propyl alcohol rectification whole-process quality management and risk early warning

Abstract

The application discloses a kind of for propanol rectification whole-process quality management and risk early warning method, it is related to propanol rectification quality risk management technical field, comprising: the mapping of establishing working condition time period and product tank section;The deviation sequence of tower top pressure, key plate temperature and product water content is generated;Main correlation degree and lag ring intensity are calculated;Based on the normalized temperature fluctuation amplitude, construct temperature control correction term, calculate time period risk index;Risk is collected to product tank section, combined with flow and value coefficient to calculate work order priority, generate adjustment queue.The application can effectively identify the water content lag drift caused by pressure fluctuation, reduce management delay and disposal cost.

Description

Technical Field

[0001] This invention relates to the field of propanol distillation quality risk management technology, and in particular to a method for quality control and risk warning throughout the propanol distillation process. Background Technology

[0002] Propanol, as a key organic chemical raw material and solvent, is typically refined using distillation technology to remove moisture and impurities. The water content of the product is a core indicator for determining whether the finished product is qualified. In industrial continuous distillation production, the gas-liquid equilibrium state directly determines the separation effect. This equilibrium state is highly sensitive to the top pressure and critical plate temperature, especially in the operating range involving azeotropic or near-azeotropic conditions. The top pressure is often affected by factors such as fluctuations in condensation load, changes in the state of the cooling medium, or the emission of non-condensable gases, and often exhibits unavoidable low-frequency fluctuations. This unsteady pressure change dynamically alters the relative volatility and azeotropic composition of the components, causing the mass transfer equilibrium boundary within the distillation column to shift, which in turn leads to deviations in the product composition distilled from the top of the column.

[0003] Existing quality control systems primarily rely on distributed control systems (DCS) for setpoint control of single process variables and periodic sampling and analysis in laboratories. In actual operation, to maintain apparent stability, control systems are often configured to forcefully maintain a constant temperature on critical plates. Under this strategy, when the pressure at the top of the column fluctuates slowly, although the temperature curve remains flat, the actual gas-liquid composition has already drifted to maintain thermodynamic equilibrium. Because distillation columns contain numerous plates or packing material, the transmission of this compositional change caused by pressure fluctuations to the product at the top of the column has a significant time lag. Existing monitoring methods typically only focus on whether instantaneous values ​​exceed limits, lacking the ability to quantitatively analyze the dynamic correlation and time lag between pressure changes and component responses. This makes it difficult to detect the lagging drift in product water content even when the temperature appears stable. Often, by the time laboratory analysis results detect the issue laggingly, a large amount of substandard material has already entered the finished product tank area, resulting in high costs for isolation, transfer, or rework. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies that fail to effectively identify product water content lag caused by fluctuations in column top pressure when the critical plate temperature is apparently stable, resulting in delayed quality control. Therefore, this invention proposes a method for quality control and risk warning throughout the propanol distillation process.

[0005] To address the problems existing in the prior art, the present invention adopts the following technical solution:

[0006] A method for quality control and risk warning throughout the propanol distillation process includes:

[0007] S1. Distillation production data is divided into operating time periods, and the time period values ​​of column top pressure, critical plate temperature, product water content, and finished product flow rate are obtained respectively. The mapping relationship between operating time periods and finished product tank sections is established.

[0008] S2. Generate pressure deviation sequence, temperature deviation sequence and product water content deviation sequence based on the time period values ​​of tower top pressure, critical plate temperature, and product water content;

[0009] S3. Determine the main correlation based on the tower top pressure deviation sequence and the product water content deviation sequence;

[0010] S4. Calculate the hysteresis loop strength based on the trajectory of the tower top pressure deviation value and the product water content deviation value;

[0011] S5. Calculate the time-period risk index based on temperature deviation sequence, main correlation, and hysteresis loop strength;

[0012] S6. Based on the mapping relationship between working time periods and finished product tank sections, the time period risk index is aggregated to the corresponding finished product tank section, and the work order priority is calculated based on the finished product flow time period value. An execution queue is generated according to the work order priority.

[0013] Preferably, the time period values ​​of the tower top pressure, critical plate temperature, product water content, and finished product flow rate are all obtained by calculating the arithmetic mean of the sampling points within the same operating condition time period.

[0014] Preferably, the generation of pressure deviation sequences, temperature deviation sequences, and product water content deviation sequences based on the time-period values ​​of pressure at the top of the tower, the time-period values ​​of temperature on the critical plate, and the time-period values ​​of product water content includes:

[0015] Within a preset rolling window length, calculate the median baseline of the tower top pressure time period value, the critical plate temperature time period value, and the product water content time period value, respectively;

[0016] The differences between the values ​​for each time period and the corresponding median baseline are calculated to form pressure deviation series, temperature deviation series and product water content deviation series.

[0017] Preferably, the main correlation is determined based on the column top pressure deviation sequence and the product water content deviation sequence, including:

[0018] The column top pressure deviation sequence remains unchanged, while the product water content deviation sequence is shifted for different time lengths within the preset maximum search time lag range;

[0019] Calculate the normalized cross-correlation coefficients of the shifted product water content deviation sequence and the column top pressure deviation sequence, respectively;

[0020] The normalized cross-correlation coefficient with the largest absolute value is taken as the principal correlation coefficient.

[0021] Preferably, the hysteresis loop strength is calculated based on the trajectory of the deviation value of the tower top pressure and the deviation value of the product water content, including:

[0022] A time series trajectory within a rolling window is constructed using the tower top pressure deviation value as the horizontal axis and the product water content deviation value as the vertical axis.

[0023] Calculate the absolute value of the area of ​​the discrete line integral formed by the time series trajectory in the coordinate plane;

[0024] Calculate the median of the absolute values ​​of the column top pressure deviation and the median of the absolute values ​​of the product water content deviation within the rolling window to obtain the column top pressure normalization factor and the product water content normalization factor.

[0025] The hysteresis loop strength is obtained by dividing the absolute value of the discrete line integral area by the product of the column top pressure normalization factor and the product water content normalization factor.

[0026] Preferably, the time-period risk index is calculated based on the temperature deviation sequence, main correlation, and hysteresis loop strength, including:

[0027] The ratio of the absolute value of the pressure deviation at the top of the tower to the pressure normalization factor at the top of the tower is used as the normalized pressure disturbance amplitude.

[0028] Calculate the median of the absolute values ​​of temperature deviations within the rolling window to obtain the temperature normalization factor;

[0029] The ratio of the absolute value of the temperature deviation to the temperature normalization factor is used as the normalized temperature fluctuation range.

[0030] The basic risk value is obtained by multiplying the principal correlation, hysteresis loop strength, and normalized pressure disturbance amplitude.

[0031] A temperature control correction term is constructed based on the normalized temperature fluctuation amplitude, and the value of the temperature control correction term is negatively correlated with the normalized temperature fluctuation amplitude.

[0032] Multiplying the base risk value by the temperature control correction term yields the period risk index.

[0033] Preferably, based on the mapping relationship between operating time periods and finished product tank sections, the time period risk index is aggregated to the corresponding finished product tank section, and the work order priority is calculated based on the finished product flow time period value, including:

[0034] For all operating periods belonging to the same finished product tank section, calculate the product of the risk index of each period and the finished product flow rate period value and the sampling period to obtain the cumulative risk of each period;

[0035] The total cumulative flow of the finished product tank section is obtained by multiplying the product flow rate of all operating periods belonging to the same finished product tank section by the sampling period.

[0036] The risk value of a tank section is obtained by summing the cumulative risk amounts for all operating periods within the finished product tank section and dividing by the total cumulative flow of the finished product tank section.

[0037] The weighting factor is obtained by multiplying the total cumulative flow of the finished product tank section by the preset unit product value coefficient;

[0038] Multiply the risk value of the tank section by a weighting factor to obtain the work order priority of the finished tank section.

[0039] Preferably, generating an execution queue based on work order priority includes:

[0040] Based on the numerical value of the work order priority, different finished tank sections are sorted in descending order to form tank section isolation work order queues, encrypted inspection work order queues, and release and shipment adjustment work order queues.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. This invention constructs a deviation sequence between the top pressure of the tower and the water content of the product, calculates the main correlation using translational alignment within the maximum search time lag range, quantifies the correlation strength between the two under the optimal time lag, and combines the hysteresis loop strength calculated based on the discrete line integral area to accurately characterize the component response hysteresis loop scale caused by low-frequency pressure fluctuations. At the same time, a temperature control correction term that is negatively correlated with the normalized temperature fluctuation amplitude is introduced. When the critical plate temperature is strongly controlled and appears to be stable, the risk index can be maintained or improved through the correction term, thereby effectively revealing the gas-liquid composition drift risk that is ignored due to the temperature control masking effect, and realizing the early identification and quantitative characterization of quality hazards in the pressure-sensitive azeotropic region.

[0043] 2. This invention establishes a dynamic mapping mechanism between working periods and finished product tank sections. It aggregates discrete time-period risk indices into an overall risk value for the finished product tank section based on flow rate weights. It also generates work order priorities by combining the total cumulative flow of the finished product tank section with the unit product value coefficient, thus constructing a comprehensive evaluation system that takes into account both the degree of quality risk and the weight of economic value. Based on the execution queue automatically generated by this priority, it can guide orderly resource scheduling and risk prevention before the finished product leaves the factory, reducing the probability of unqualified materials entering the finished product circulation process and the subsequent rework costs. Attached Figure Description

[0044] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0045] Figure 1This is a schematic diagram of a method for quality control and risk warning of the entire propanol distillation process, provided in an embodiment of the present invention. Detailed Implementation

[0046] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0047] Example: This example provides a method for quality control and risk warning throughout the entire propanol distillation process. See [link to example]. Figure 1 Specifically, including:

[0048] S1. Distillation production data is divided into operating time periods, and the time period values ​​of column top pressure, critical plate temperature, product water content, and finished product flow rate are obtained respectively. The mapping relationship between operating time periods and finished product tank sections is established.

[0049] In embodiments of the present invention, distillation production data is divided into operating time periods, and the time period values ​​of column top pressure, critical plate temperature, product water content, and finished product flow rate are obtained respectively. A mapping relationship between operating time periods and finished product tank sections is established, including:

[0050] Data on the top pressure, critical plate temperature, product water content, and finished product flow rate of propanol distillation process are collected. The continuous production process is discretized into multiple operating time periods, and a mapping relationship between the operating time periods and the finished product tank section is established.

[0051] The arithmetic mean of the sampling points within the same operating condition period was calculated to obtain the time values ​​of tower top pressure, critical plate temperature, product water content, and finished product flow rate.

[0052] Specifically, propanol distillation refers to the continuous operation of a mixture with propanol as the main component, in a distillation column, where components are separated through vapor-liquid phase change and mass and heat transfer. The top pressure is the pressure state quantity jointly embodied by the vapor space at the top of the distillation column and its connected reflux condenser system. It reflects the degree of compression of the top vapor phase and changes in condensation load, and affects the boiling point and vapor-liquid equilibrium within the column. The critical plate temperature is the temperature at a selected representative plate or packing height within the distillation column, used to characterize the comprehensive result of vapor-liquid phase composition and mass transfer intensity near that location. The product water content is the proportion of water component in the product distilled from the top of the column or obtained from a designated collection point, directly reflecting the degree of dehydration and the product purity boundary. The finished product flow rate is the volume or mass of product entering the finished product system per unit time, reflecting the output intensity and determining the accumulation rate of material in subsequent tank areas. The finished product tank section refers to the continuous time interval of finished product entering the same finished product tank and its corresponding material accumulation interval.

[0053] In detail, when collecting data on the top pressure, critical plate temperature, product water content, and finished product flow rate during the propanol distillation process, a pressure sampling point is first set up at the gas-to-gas connection section at the top of the distillation column, and the raw value of the top pressure is read at a fixed sampling period. The raw value of the critical plate temperature is read at the temperature measuring point at the height of the critical plate. The raw value of the product water content is generated from the online moisture analyzer on the product collection pipeline or backfilled from laboratory test results. The raw value of the finished product flow rate is read from the flow meter on the finished product delivery pipeline. The sampling period is preferably one to ten minutes to balance the capture of low-frequency fluctuations in the top pressure due to condensation load and the suppression of on-site noise. Simultaneously, to ensure that all data items are collected at the same time... The following methods can be directly aligned: the original values ​​of tower top pressure, critical plate temperature, product water content, and finished product flow rate are synchronized and aligned according to the sampling timestamp. If the sampling frequency of a certain data item is higher than the preset sampling period, it is summarized into the representative value of that period within the preset sampling period. If the sampling frequency of a certain data item is lower than the preset sampling period, its result is marked to the operating time period covering the effective range of the result, and the operating time period value within the effective range is filled according to the unchanged rule, thereby forming the tower top pressure time period value, critical plate temperature time period value, product water content time period value, and finished product flow rate time period value arranged by the operating time period index, where each operating time period corresponds to a continuous time interval.

[0054] The time axis is segmented with a preset sampling period, and the arithmetic mean of the sampling points in each segment is calculated to obtain the corresponding time period value to reduce the impact of instantaneous fluctuations on subsequent calculations. The average number of sampling points used is preferably no less than three to reduce the disturbance of occasional spikes to the time period value. When establishing the mapping relationship between the working condition time period and the finished product tank section, the tank entry switching record or valve position opening and closing status and tank number identifier of the finished product tank area are first obtained. The switching record includes at least the switching time and the current target tank number. The continuous tank entry interval between two adjacent switching times is defined as the finished product tank section, so that each finished product tank section corresponds to a unique target tank number. Then, the time interval of each working condition time period and the time interval of the finished product tank section are overlapped to determine the finished product tank section corresponding to the working condition time period. If a certain working condition time period spans the switching time of the finished product tank section, the working condition time period is allocated to multiple finished product tank sections according to the proportion of the finished product flow in each finished product tank section within the working condition time period, and the corresponding weight is recorded. The weight is determined by the time length of each finished product tank section within the working condition time period and the finished product flow time period value. Thus, a mapping relationship table with the working condition time period as the index and the finished product tank section as the output is obtained.

[0055] S2. Generate pressure deviation sequence, temperature deviation sequence and product water content deviation sequence based on the time period values ​​of tower top pressure, critical plate temperature, and product water content;

[0056] In embodiments of the present invention, pressure deviation sequences, temperature deviation sequences, and product water content deviation sequences are generated based on the tower top pressure time period value, the critical plate temperature time period value, and the product water content time period value, including:

[0057] Within a preset rolling window length, calculate the median baseline of the tower top pressure time period value, the critical plate temperature time period value, and the product water content time period value, respectively;

[0058] Calculate the difference between the value of each time period and the corresponding median baseline to form pressure deviation series, temperature deviation series and product water content deviation series;

[0059] Specifically, a time period index sequence is first established for the discretized operating time periods according to time sequence. For each current operating time period, several consecutive operating time periods tracing back to it are selected to form a rolling window. The length of the rolling window is denoted by a preset length and is preferably between 60 and 360 operating time periods to cover the operating range of one hour to twenty-four hours. This ensures that the low-frequency slow fluctuations in the tower top pressure caused by the condensation load and ambient cooling conditions are fully contained, and that the interference of instantaneous noise on the baseline is suppressed. After forming the rolling window, all tower top pressure time period values ​​within the rolling window are extracted and sorted in ascending order. If the number of time periods within the window is odd, the value at the middle position after sorting is taken as the median baseline of the tower top pressure. If the number of time periods within the window is even, the arithmetic mean of the two middle values ​​after sorting is taken as the median baseline of the tower top pressure. Similarly, the same sorting and value-taking rules are applied to all critical plate temperature time period values ​​and all product water content time period values ​​within the rolling window to obtain the median baseline of the critical plate temperature and the median baseline of the product water content. To ensure that the baseline calculation is within the sequence... The initial phase can be implemented. When the available operating time periods before the current operating time period are less than the preset rolling window length, all actual available operating time periods are included in the rolling window and the median baseline is calculated according to the same rules. Then, the difference between each time period value and the corresponding median baseline is calculated to form a deviation sequence. Specifically, for each current operating time period, the pressure deviation value of the tower top pressure period is obtained by subtracting the median baseline of the tower top pressure from the tower top pressure period value of the operating time period. The pressure deviation values ​​of all operating time periods are arranged in chronological order to form a pressure deviation sequence. The temperature deviation value of the critical plate temperature period is obtained by subtracting the median baseline of the critical plate temperature from the critical plate temperature period value of the operating time period and is arranged in chronological order to form a temperature deviation sequence. The product water content period value of the operating time period is obtained by subtracting the median baseline of the product water content from the product water content period value and is arranged in chronological order to form a product water content deviation sequence. The reason for using the median baseline instead of the arithmetic mean baseline is that the median is not sensitive to occasional spikes and short-term anomalies and can stably characterize the steady-state center level of the operating time period.

[0060] S3. Determine the principal correlation degree based on the time lag correlation between the column top pressure deviation sequence and the product water content deviation sequence;

[0061] In an embodiment of the present invention, determining the primary correlation based on the column top pressure deviation sequence and the product water content deviation sequence includes:

[0062] The column top pressure deviation sequence remains unchanged, while the product water content deviation sequence is shifted for different time lengths within the preset maximum search time lag range;

[0063] Calculate the normalized cross-correlation coefficients of the shifted product water content deviation sequence and the column top pressure deviation sequence, respectively;

[0064] The normalized cross-correlation coefficient with the largest absolute value is taken as the main correlation coefficient;

[0065] It should be noted that the principal correlation coefficient refers to the maximum absolute value of the normalized cross-correlation coefficient calculated for each shift length within the preset maximum search time lag range, after keeping the top pressure deviation sequence unchanged and aligning the product water content deviation sequence according to different time lengths. It is used to characterize the degree of synchronous change and correlation strength between the top pressure deviation sequence and the product water content deviation sequence under a certain optimal time lag alignment condition. The larger the principal correlation coefficient value, the more significant the same-direction or opposite linkage between the two under the optimal time lag, thus reflecting the significance of the product water content lag drift caused by the low-frequency fluctuation of the top pressure during propanol distillation.

[0066] Specifically, to determine the primary correlation, the operating periods are first numbered sequentially to form a column top pressure deviation sequence and a product water content deviation sequence. The two sequences are then matched item by item under the same operating period index. The column top pressure deviation sequence is then kept unchanged as a reference sequence, and a maximum search lag is set as the upper bound of the preset maximum search lag range. This maximum search lag is calculated based on the number of operating periods, preferably six to one hundred and twenty, to cover the typical lag interval of column top pressure disturbances transmitted to product water content via column residence time and mass transfer inertia, while also ensuring controllable computational load. Based on this, candidate translation lengths are enumerated one by one from the zero operating period to the maximum search lag. For each candidate translation length, the product water content deviation sequence is shifted backward along the time axis by that candidate translation length, aligning the items in the earlier operating period of the product water content deviation sequence with the items in the later operating period of the column top pressure deviation sequence. This constructs an alignment interval under that candidate translation length. The alignment interval is the set of operating periods where the two sequences overlap to ensure consistent indices when multiplying item by item.

[0067] Within the alignment interval, normalized cross-correlation coefficients are calculated. First, the column top pressure deviation value and the shifted product water content deviation value within the alignment interval are multiplied item by item and summed to obtain the correlation term. Then, the column top pressure deviation value within the alignment interval is squared item by item, summed, and the square root is taken to obtain the first amplitude term. The shifted product water content deviation value within the alignment interval is squared item by item, summed, and the square root is taken to obtain the second amplitude term. The ratio of the correlation term to the product of the first and second amplitude terms is determined as the normalized cross-correlation coefficient corresponding to the candidate shift length. The above shifting and calculation process is repeated for all candidate shift lengths to obtain a set of normalized cross-correlation coefficient sequences. Finally, the absolute value of this set of normalized cross-correlation coefficients is taken, and the normalized cross-correlation coefficient with the largest absolute value is selected as the principal correlation coefficient. This allows the principal correlation coefficient to characterize the correlation strength between the column top pressure deviation sequence and the product water content deviation sequence under optimal time-delay alignment conditions.

[0068] S4. Calculate the hysteresis loop strength based on the trajectory of the tower top pressure deviation value and the product water content deviation value;

[0069] In an embodiment of the present invention, the hysteresis loop strength is calculated based on the trajectory of the deviation value of the tower top pressure and the deviation value of the product water content, including:

[0070] A time series trajectory within a rolling window is constructed using the tower top pressure deviation value as the horizontal axis and the product water content deviation value as the vertical axis.

[0071] Calculate the absolute value of the area of ​​the discrete line integral formed by the time series trajectory in the coordinate plane;

[0072] Specifically, to construct the time series trajectory within the rolling window and calculate the absolute value of the discrete line integral area formed by it in the coordinate plane, the set of continuous operating time periods participating in the calculation is first determined within the preset rolling window length corresponding to the current operating time period. Then, the tower top pressure deviation value and product water content deviation value for each operating time period are read sequentially from this set in chronological order. A pair of deviation values ​​corresponding to each operating time period is grouped into a two-dimensional coordinate point, with the tower top pressure deviation value as the abscissa and the product water content deviation value as the ordinate, thus obtaining a point sequence arranged in chronological order. Subsequently, adjacent point pairs in the point sequence are connected sequentially to form the time series trajectory, which reflects the joint change path of the tower top pressure deviation and product water content deviation as the operating condition evolves over time. When calculating the discrete line integral area, two adjacent coordinate points are considered as a segment of the trajectory. The arithmetic mean of the ordinates of the two ends of the line segment is taken as the representative ordinate of the segment, and the difference between the abscissas of the two ends is taken as the lateral increment of the segment. The representative ordinate is multiplied by the lateral increment to obtain the discrete integral increment of the segment. The discrete integral increments of all adjacent point pairs within the rolling window are accumulated in time order to obtain the discrete linear integral area. The sign of this area is used to characterize the circumferential direction of the lag loop formed by the trajectory, and its absolute value is used to characterize the size of the loop. In order to avoid the instability of the area due to insufficient number of trajectory segments caused by the rolling window being too short, the preset rolling window length is preferably 60 to 360 working period periods to cover the operating range of one hour to 24 hours. This can suppress the disturbance of instantaneous noise on the trajectory shape while including the low-frequency fluctuation process of the tower top pressure. Finally, the absolute value of the accumulated discrete linear integral area is taken as the absolute value of the area output.

[0073] Calculate the median of the absolute values ​​of the column top pressure deviation and the median of the absolute values ​​of the product water content deviation within the rolling window to obtain the column top pressure normalization factor and the product water content normalization factor.

[0074] The hysteresis loop strength is obtained by dividing the absolute value of the discrete line integral area by the product of the column top pressure normalization factor and the product water content normalization factor.

[0075] It should be noted that the hysteresis loop strength refers to the quantitative result of the hysteresis loop formed in the coordinate plane by the time series trajectory with the column top pressure deviation value as the abscissa and the product water content deviation value as the ordinate within a preset rolling window length. In its calculation, the arithmetic mean of the difference of the abscissa of adjacent points of the trajectory and the ordinate of the two ends is accumulated segment by segment to obtain the discrete line integral area, and the absolute value of the discrete line integral area is taken as the hysteresis loop area. Then, the hysteresis loop area is normalized by the median of the absolute value of the column top pressure deviation and the median of the absolute value of the product water content deviation within the rolling window, respectively. This makes the hysteresis loop strength numerically insensitive to occasional spikes and short-term anomalies, and can stably characterize the degree of cyclic hysteresis formed by the time lag drift of product water content caused by column top pressure fluctuations during propanol distillation. The larger the hysteresis loop strength value, the more obvious the hysteresis loop between the two and the more prominent the resulting quality risk.

[0076] Specifically, to obtain the normalization factor for the tower top pressure and the normalization factor for the product water content, and to further calculate the hysteresis loop strength, a set of continuous operating periods for calculation is first determined within the preset rolling window length corresponding to the current operating period. The tower top pressure deviation value and the product water content deviation value for each operating period within this set are then extracted. The absolute values ​​of the tower top pressure deviation values ​​are taken one by one to form a sequence of absolute values ​​for the tower top pressure deviation, and the absolute values ​​of the product water content deviation values ​​are taken one by one to form a sequence of absolute values ​​for the product water content deviation. Subsequently, the two absolute value sequences are sorted from smallest to largest to calculate the median. When the number of operating periods within the rolling window is odd, the value in the middle position after sorting is taken as the median. When the number of time periods is even, the arithmetic mean of the two middle items after sorting is taken as the median. Thus, the median of the absolute value sequence of the top pressure deviation is determined as the top pressure normalization factor, and the median of the absolute value sequence of the product water content deviation is determined as the product water content normalization factor. The reason for using the median instead of the arithmetic mean as the normalization factor is that the median is not sensitive to occasional spikes and short-term anomalies, and can provide a stable scale reference for different operating condition windows. Then, the absolute value of the integral area of ​​the discrete line is read and divided by the product of the top pressure normalization factor and the product water content normalization factor to obtain the hysteresis loop strength, thereby obtaining a hysteresis loop strength result that is comparable under different pressure disturbance amplitudes and different water content fluctuation scales.

[0077] S5. Calculate the time-period risk index based on temperature deviation sequence, main correlation, and hysteresis loop strength;

[0078] In embodiments of the present invention, the time-period risk index is calculated based on the temperature deviation sequence, principal correlation, and hysteresis loop strength, including:

[0079] The ratio of the absolute value of the pressure deviation at the top of the tower to the pressure normalization factor at the top of the tower is used as the normalized pressure disturbance amplitude.

[0080] Calculate the median of the absolute values ​​of temperature deviations within the rolling window to obtain the temperature normalization factor;

[0081] The ratio of the absolute value of the temperature deviation to the temperature normalization factor is used as the normalized temperature fluctuation range.

[0082] The basic risk value is obtained by multiplying the principal correlation, hysteresis loop strength, and normalized pressure disturbance amplitude.

[0083] It should be noted that the basic risk value refers to the risk characterization quantity obtained by multiplying the principal correlation, hysteresis loop strength, and normalized pressure disturbance amplitude within the current operating period. The principal correlation reflects the correlation strength between the top pressure deviation sequence and the product water content deviation sequence under the optimal time lag alignment condition. The hysteresis loop strength reflects the lap lag scale formed by the evolution of the top pressure deviation and the product water content deviation over time. The normalized pressure disturbance amplitude reflects the relative deviation of the current top pressure deviation from the typical pressure fluctuation scale within the rolling window. Therefore, the basic risk value can simultaneously and comprehensively characterize whether the delayed correlation between pressure disturbance and product water content change is significant and whether the current pressure disturbance is at an abnormal level. The larger the basic risk value, the more prominent the potential for delayed deviation in product water content caused by pressure fluctuation within the operating period.

[0084] Specifically, to obtain the normalized pressure disturbance amplitude, temperature normalization factor, normalized temperature fluctuation amplitude, and basic risk value, the tower top pressure deviation value corresponding to the current operating condition period is first read, and its absolute value is taken to obtain the absolute value of the tower top pressure deviation. Simultaneously, the tower top pressure normalization factor calculated within the same rolling window is read. The absolute value of the tower top pressure deviation is compared with the tower top pressure normalization factor to obtain the normalized pressure disturbance amplitude. This amplitude characterizes the relative degree to which the current tower top pressure deviates from the steady-state center level and eliminates the incomparability caused by pressure magnitude differences under different operating conditions. Subsequently, the temperature deviation sequence is extracted within the rolling window length corresponding to the current operating condition period, and the absolute value of each item is taken to obtain the absolute value of the temperature deviation. For the temperature deviation absolute value sequence, sort the sequence by value from smallest to largest and take the median as the temperature normalization factor. Then, read the temperature deviation value of the current operating period and take its absolute value to obtain the absolute value of the temperature deviation. Compare the absolute value of the temperature deviation with the temperature normalization factor to obtain the normalized temperature fluctuation amplitude, which is used to characterize the relative level of the current temperature fluctuation relative to the typical fluctuation scale within the window. Read the obtained principal correlation degree and hysteresis loop strength, and synthesize the principal correlation degree, hysteresis loop strength and normalized pressure disturbance amplitude by multiplying them to obtain the basic risk value. The basic risk value reflects the optimal time lag correlation strength between the tower top pressure and the product water content, the hysteresis loop size and the relative amplitude of the current pressure disturbance.

[0085] A temperature control correction term is constructed based on the normalized temperature fluctuation amplitude, and the value of the temperature control correction term is negatively correlated with the normalized temperature fluctuation amplitude.

[0086] Multiplying the base risk value by the temperature control correction term yields the time period risk index.

[0087] It should be noted that the time period risk index refers to the risk quantification result obtained by multiplying the basic risk value and the temperature control correction term for a specific operating period. The basic risk value is used to characterize the strength of the delayed correlation between the tower top pressure fluctuation and the product water content change, the scale of the loop lag, and the relative degree of the current pressure deviating from the typical fluctuation scale. The temperature control correction term is used to reflect the corrective effect of the critical plate temperature fluctuation level on the risk quantification result. Therefore, the time period risk index can comprehensively characterize the relative strength of the potential for delayed deviation of product water content caused by tower top pressure disturbance within the operating period with a single value.

[0088] Specifically, the calculated normalized temperature fluctuation amplitude is read during the current operating period and used as an input to characterize the relative temperature fluctuation level of the critical plate. To ensure that the value of the temperature control correction term is negatively correlated with the normalized temperature fluctuation amplitude, a defined monotonically decreasing mapping rule is used to generate the temperature control correction term. Preferably, one divided by one plus the normalized temperature fluctuation amplitude is taken as the temperature control correction term. Thus, when the normalized temperature fluctuation amplitude increases, the temperature control correction term decreases according to the same rule, and when the normalized temperature fluctuation amplitude decreases, the temperature control correction term increases according to the same rule, which facilitates comparable risk correction between different operating periods. The basic risk value of the corresponding operating period is read, and the basic risk value is multiplied by the temperature control correction term to obtain the period risk index of that operating period. This allows the period risk index to retain the delayed correlation and loop size information reflected by the main correlation and lag loop strength, while introducing the suppression or amplification effect of the critical plate temperature fluctuation level on risk.

[0089] S6. Based on the mapping relationship between working time periods and finished product tank sections, the time period risk index is aggregated to the corresponding finished product tank section, and the work order priority is calculated in combination with the finished product flow time period value. An execution queue is generated according to the work order priority.

[0090] In an embodiment of the present invention, based on the mapping relationship between working time periods and finished product tank sections, the time period risk index is aggregated to the corresponding finished product tank section, and the work order priority is calculated in conjunction with the finished product flow time period value. An execution queue is then generated based on the work order priority, including:

[0091] For all operating periods belonging to the same finished product tank section, calculate the product of the risk index of each period and the finished product flow rate period value and the sampling period to obtain the cumulative risk of each period;

[0092] The total cumulative flow of the finished product tank section is obtained by multiplying the product flow rate of all operating periods belonging to the same finished product tank section by the sampling period.

[0093] Specifically, based on the mapping relationship between operating time periods and finished product tank sections, the set of operating time periods corresponding to the target finished product tank section is determined. Within this set, the time period risk index, finished product flow time period value, and sampling period are read sequentially for each operating time period. When calculating the cumulative risk of each time period, the time period risk index of each operating time period is multiplied by the finished product flow time period value of that operating time period and further multiplied by a preset sampling period to obtain the cumulative risk of that operating time period. This cumulative risk can characterize the risk contribution accumulated with the amount of finished product shipped out during that operating time period and avoids ignoring the production difference caused by averaging only the time period risk index. The finished product flow time period value is multiplied by the sampling period to obtain the cumulative flow of that operating time period. The cumulative flow of all operating time periods corresponding to the finished product tank section is accumulated sequentially to obtain the total cumulative flow of the finished product tank section. This total cumulative flow reflects the amount of finished product passing through the corresponding tank section.

[0094] The risk value of a tank section is obtained by summing the cumulative risk amounts for all operating periods within the finished product tank section and dividing by the total cumulative flow of the finished product tank section.

[0095] The weighting factor is obtained by multiplying the total cumulative flow of the finished product tank section by the preset unit product value coefficient;

[0096] Multiply the risk value of the tank section by a weighting factor to obtain the work order priority of the finished tank section;

[0097] Specifically, for the target finished product tank segment, a set of all corresponding operating time periods is compiled, and the calculated cumulative risk amount for each operating time period in the set and the total cumulative flow of the finished product tank segment are read. Based on this, the cumulative risk amounts for all operating time periods in the finished product tank segment are summed to obtain the total cumulative risk of the tank segment. The total cumulative risk of the tank segment is then divided by the total cumulative flow of the finished product tank segment to obtain the tank segment risk value. This tank segment risk value represents the average risk level corresponding to the unit finished product throughput and eliminates the incomparability caused by differences in tank entry time or output between different finished product tank segments. Subsequently, a preset unit product value coefficient is read and multiplied by the total cumulative flow of the finished product tank segment to obtain a weighting factor. The unit product value coefficient is preferably determined by the ratio of the net sales revenue to the outbound quantity of the target propanol product in the statistical period to reflect the unit value level of the same product in the statistical period. Finally, the tank segment risk value is multiplied by the weighting factor to obtain the work order priority of the finished product tank segment, so that the work order priority simultaneously reflects the tank segment risk level and the finished product scale and unit value weight corresponding to the tank segment.

[0098] Based on the numerical value of the work order priority, different finished tank sections are sorted in descending order to form tank section isolation work order queue, encrypted inspection work order queue, and release and shipment adjustment work order queue, respectively.

[0099] Specifically, within the statistical period or within the current batch to be processed, the work order priorities of all finished tank segments are obtained. For each finished tank segment, a record is created containing the segment identifier, corresponding tank entry time interval, segment risk value, total cumulative flow, and work order priority. Then, all finished tank segment records are sorted in descending order using the work order priority as the sorting key to obtain a unified priority processing sequence, ensuring that finished tank segments with higher work order priority values ​​appear earlier in the sequence. To ensure the determinism of the sorting, when finished tank segments with the same work order priority value are encountered, a secondary sorting rule is used, prioritizing those with higher risk values. If the risk values ​​are still the same, a tertiary sorting rule is used, prioritizing those with larger total cumulative flow. If a distinction still cannot be made, a final sorting rule is used, prioritizing those with earlier tank entry times, thus forming an unambiguous sort. The order of the three types of execution queues is as follows: When forming a tank segment isolation work order queue, the order of ...

[0100] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for quality control and risk warning throughout the entire propanol distillation process, characterized in that, Includes the following steps: S1. Distillation production data is divided into operating time periods, and the time period values ​​of column top pressure, critical plate temperature, product water content, and finished product flow rate are obtained respectively. The mapping relationship between operating time periods and finished product tank sections is established. S2. Generate pressure deviation sequence, temperature deviation sequence and product water content deviation sequence based on the tower top pressure time period value, key plate temperature time period value and product water content time period value; The specific steps for generating pressure deviation sequences, temperature deviation sequences, and product moisture content deviation sequences based on the time-period values ​​of tower top pressure, critical plate temperature, and product moisture content are as follows: Within a preset rolling window length, calculate the median baseline of the tower top pressure time period value, the critical plate temperature time period value, and the product water content time period value, respectively; Calculate the difference between the value of each time period and the corresponding median baseline to form pressure deviation series, temperature deviation series and product water content deviation series; S3. Determine the main correlation based on the tower top pressure deviation sequence and the product water content deviation sequence; The specific steps for determining the principal correlation based on the column top pressure deviation sequence and the product water content deviation sequence are as follows: The column top pressure deviation sequence remains unchanged, while the product water content deviation sequence is shifted for different time lengths within the preset maximum search time lag range; Calculate the normalized cross-correlation coefficients of the shifted product water content deviation sequence and the column top pressure deviation sequence, respectively; The normalized cross-correlation coefficient with the largest absolute value is taken as the main correlation coefficient; S4. Calculate the hysteresis loop strength based on the trajectory of the tower top pressure deviation value and the product water content deviation value; The specific steps for calculating the hysteresis loop strength based on the trajectory of the tower top pressure deviation and the product water content deviation are as follows: A time series trajectory within a rolling window is constructed using the tower top pressure deviation value as the horizontal axis and the product water content deviation value as the vertical axis. Calculate the absolute value of the area of ​​the discrete line integral formed by the time series trajectory in the coordinate plane; Calculate the median of the absolute values ​​of the column top pressure deviation and the median of the absolute values ​​of the product water content deviation within the rolling window to obtain the column top pressure normalization factor and the product water content normalization factor. The hysteresis loop strength is obtained by dividing the absolute value of the discrete line integral area by the product of the column top pressure normalization factor and the product water content normalization factor. S5. Calculate the time-period risk index based on temperature deviation sequence, main correlation, and hysteresis loop strength; The specific steps for calculating the time-period risk index based on temperature deviation series, main correlation, and hysteresis loop strength are as follows: The ratio of the absolute value of the pressure deviation at the top of the tower to the pressure normalization factor at the top of the tower is used as the normalized pressure disturbance amplitude. Calculate the median of the absolute values ​​of temperature deviations within the rolling window to obtain the temperature normalization factor; The ratio of the absolute value of the temperature deviation to the temperature normalization factor is used as the normalized temperature fluctuation range. The basic risk value is obtained by multiplying the principal correlation, hysteresis loop strength, and normalized pressure disturbance amplitude. A temperature control correction term is constructed based on the normalized temperature fluctuation amplitude, and the value of the temperature control correction term is negatively correlated with the normalized temperature fluctuation amplitude. Multiplying the base risk value by the temperature control correction term yields the time period risk index. S6. Based on the mapping relationship between working time periods and finished product tank sections, the time period risk index is aggregated to the corresponding finished product tank section, and the work order priority is calculated based on the finished product flow time period value. An execution queue is generated according to the work order priority.

2. The method for quality control and risk warning throughout the propanol distillation process according to claim 1, characterized in that, The time-period values ​​of tower top pressure, critical plate temperature, product water content, and finished product flow rate were all obtained by calculating the arithmetic mean of the sampling points within the same operating condition time period.

3. The method for quality control and risk warning throughout the propanol distillation process according to claim 1, characterized in that, Based on the mapping relationship between operating time periods and finished product tank sections, the time period risk index is aggregated to the corresponding finished product tank section, and the work order priority is calculated based on the finished product flow time period value, including: For all operating periods belonging to the same finished product tank section, calculate the product of the risk index of each period and the finished product flow rate period value and the sampling period to obtain the cumulative risk of each period; The total cumulative flow of the finished product tank section is obtained by multiplying the product flow rate of all operating periods belonging to the same finished product tank section by the sampling period. The risk value of a tank section is obtained by summing the cumulative risk amounts for all operating periods within the finished product tank section and dividing by the total cumulative flow of the finished product tank section. The weighting factor is obtained by multiplying the total cumulative flow of the finished product tank section by the preset unit product value coefficient; Multiply the risk value of the tank section by a weighting factor to obtain the work order priority of the finished tank section.

4. The method for quality control and risk warning of the entire propanol distillation process according to claim 1, characterized in that, An execution queue is generated based on the work order priority, including: Based on the numerical value of the work order priority, different finished tank sections are sorted in descending order to form tank section isolation work order queues, encrypted inspection work order queues, and release and shipment adjustment work order queues.

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