WO2020006779A1 - 一种机械密封智能调节系统与方法 - Google Patents

一种机械密封智能调节系统与方法 Download PDF

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Publication number
WO2020006779A1
WO2020006779A1 PCT/CN2018/095757 CN2018095757W WO2020006779A1 WO 2020006779 A1 WO2020006779 A1 WO 2020006779A1 CN 2018095757 W CN2018095757 W CN 2018095757W WO 2020006779 A1 WO2020006779 A1 WO 2020006779A1
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Prior art keywords
seal
state
module
link
adjustment
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English (en)
French (fr)
Inventor
黄伟峰
刘向锋
尹源
刘莹
李德才
李永健
索双富
王子羲
贾晓红
郭飞
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Tsinghua University
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Tsinghua University
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Priority to US17/257,535 priority Critical patent/US11199264B2/en
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16J—PISTONS; CYLINDERS; SEALINGS
    • F16J15/00—Sealings
    • F16J15/16—Sealings between relatively-moving surfaces
    • F16J15/34—Sealings between relatively-moving surfaces with slip-ring pressed against a more or less radial face on one member
    • F16J15/3492—Sealings between relatively-moving surfaces with slip-ring pressed against a more or less radial face on one member with monitoring or measuring means associated with the seal
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16J—PISTONS; CYLINDERS; SEALINGS
    • F16J15/00—Sealings
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/005—Sealing rings
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Program-control systems
    • G05B19/02—Program-control systems electric
    • G05B19/04—Program control other than numerical control, i.e. in sequence controllers or logic controllers

Definitions

  • the invention belongs to the field of fluid sealing and the field of automatic control, and particularly relates to an intelligent adjustment system and method for mechanical seals.
  • Mechanical seal is a common form of shaft end seal in rotating machinery.
  • the matching dynamic and static rings rotate relative to each other to form a friction pair with certain stability, which reduces or even eliminates contact while limiting leakage.
  • the stability of this tiny design from the lubrication, dynamics, heat transfer and deformation of the seal still sometimes fails to maintain the stability of the friction pair under the influence of strong abnormal factors, resulting in a decrease in sealing performance and a shortened life. Even unpredictable failures occur.
  • the object of the present invention is to provide an intelligent adjustment system and method for mechanical seals, which, based on real-time monitoring and analysis of the seal state, finds the best and By adjusting the reachable state, the seal is adjusted to this state by the adjusting device.
  • a mechanical seal intelligent adjustment system includes:
  • Monitoring device to measure signals related to sealing in real time
  • the control device includes a state judgment module, a feasible region analysis module, an evaluation module, and an optimization module, wherein the state judgment module interprets signals obtained by the monitoring device to estimate the sealed state, and the feasible region analysis module judges according to the current state
  • the adjusting function of the adjusting device can make the seal reach the state, the evaluation module evaluates the value of the seal state, and the optimization module seeks to obtain the highest safety and / or economic benefits from the feasible region of the seal adjustment as far as possible. Adjustment method, according to which instructions are given to the adjustment device;
  • the adjusting device actively acts on the seal according to the instruction given by the control device.
  • the monitoring device mainly includes a sensor, a signal pre-processing device, a acquisition card, acquisition software, and necessary terminal equipment as a carrier.
  • the seal-related signals include upstream and downstream pressures, pressure in the membrane, rotation speed, seal ring temperature, seal ring displacement, seal ring capacitance, and friction pair acoustic emission.
  • the adjustment device exerts a force on the seal and changes pressure. , Shape change, and one or more combinations of heating / cooling.
  • the state judgment module filters the signal measured by the monitoring device and obtains the value of the measured physical quantity according to the calibration relationship.
  • the evaluation module first calculates its performance from a given seal state, and then adjusts the performance parameters according to the actual application scenario. The requirements are combined to map each sealed state into a quantity of value.
  • the invention also provides a method for intelligently adjusting a mechanical seal, which measures a seal-related signal in real time, executes a control algorithm, generates an instruction to act on the seal, and performs seal adjustment.
  • the control algorithm includes a state judgment link and is feasible Domain analysis link, evaluation link and optimization link, the state judgment link interprets the signal obtained by the monitoring device to estimate the state of the seal, and the feasible domain analysis link judges the state that the adjustment device can make the seal reach according to the current state
  • the evaluation link evaluates the value of the state of the seal, and the optimization link seeks to obtain a higher-value adjustment mode as far as possible from the feasible region of the seal adjustment, and issues instructions accordingly.
  • the measured signal is filtered and the measured physical quantity value is obtained according to the calibration relationship.
  • the state judgment algorithm gives the probability of the seal state Distribution, and make further judgments based on the adjusted signal changes.
  • the state judgment, feasible region analysis, and evaluation are based on a method of designing accurate or approximate calculations based on the characteristics model of the seal, which refers to what kind of performance and specific monitorable elements a specific state seal will bring, and How the state of the future will change.
  • Figure 1 is a typical combination of the three devices of the system of the present invention.
  • the combination can also be adjusted if necessary. Under their function, the seal can achieve the maximum value in the specific application scenario as far as possible, and achieve the purpose of precise regulation.
  • FIG. 2 is a schematic diagram of a sealing structure using a static ring floating design in Embodiment 1 of the present invention.
  • FIG. 3 is a schematic diagram of a cone height adjustment in Embodiment 1 of the present invention.
  • FIG. 4 is a schematic diagram of a sealing structure using a static ring floating design in Embodiment 2 of the present invention.
  • FIG. 5 is a schematic diagram of an end surface of the static ring in FIG. 3.
  • the present invention is a mechanical seal intelligent adjustment system. Based on real-time monitoring and analysis of the seal state, according to the comprehensive performance goals required by the user, find the best and reachable state through adjustment, and through adjustment The device adjusts the seal to this state, which includes:
  • Monitoring devices mainly include sensors, signal pre-processing devices (such as amplifiers, signal converters, etc.), acquisition cards, acquisition software, and necessary terminal equipment (such as industrial computers) as carriers.
  • the monitoring device measures a variety of signals related to the seal in real time.
  • the available signals usually include upstream and downstream pressures, pressure inside the membrane, rotation speed, seal ring temperature, seal ring displacement, seal ring capacitance, and friction pair acoustic emission.
  • control algorithm carrier The software and the terminal device running it are used as the control algorithm carrier.
  • control algorithm of the present invention mainly includes the following links: state judgment, feasible region analysis, evaluation, and optimization.
  • the state judgment section interprets the signals obtained by the monitoring device to estimate the state of the seal. It filters the measured signal and obtains the value of the measured physical quantity according to the calibration relationship. For some signal types, it is also necessary to calculate according to the corresponding seal model (for example, the temperature measured at a point in the seal ring, and the degree of friction of the seal end face is estimated based on the heat transfer analysis of the seal). Sometimes the measurement of the sensor can not provide all the information to determine the seal state. At this time, the state judgment algorithm gives a probability distribution of the seal state, and further judges based on the adjusted signal change.
  • the feasible region analysis link judges the state that the sealing device can achieve based on the current state of the adjusting device.
  • the evaluation link evaluates the condition of the seal. It first calculates its performance from a given seal state, and then integrates the performance parameters according to the needs of the actual application scenario. In general this link maps each sealed state to a value.
  • the optimization link seeks to obtain a higher-value adjustment method from the feasible region of the seal adjustment, and issues instructions to the adjustment device accordingly.
  • the state judgment, feasible region analysis, and evaluation are based on the characteristic model of the seal—that is, how the performance of the seal in a particular state will bring about, what kind of monitorable elements will be produced, and how the future state will change—design accurate or approximate calculations Methods.
  • the regulating device actively exerts an action on the seal according to the instructions given by the control algorithm (this action may be in various forms, such as force, pressure change, shape change, heating / cooling, etc., of course, it also includes a combination of multiple forms of action ).
  • a mechanical seal is used to seal non-dangerous and pollution-free materials. It is hoped that while avoiding the wear of the seal ring to avoid the cost of replacing the seal ring, it will reduce leakage as much as possible to improve material yield, and ultimately maximize economic benefits.
  • the seal adopts a static ring floating design (the static ring 1 is floatingly supported on the static ring seat 3 via a spring 4, and the secondary ring 5 is used to prevent leakage from the static ring seat 3).
  • the piezoelectric stacking ring 6 is embedded on the sealing static ring 1, which can change the cone height ⁇ of the sealing end face when the voltage is applied (see Figure 3): an increase in the cone height (this example only involves a converging cone) will increase the sealed fluid
  • the static pressure effect increases the gap between the static ring and the moving ring, thereby reducing or eliminating contact, but it will increase the amount of leakage.
  • Two miniature acoustic emission sensors 7 symmetrically arranged on the back of the static ring measure the acoustic emission signals from the sealed friction pair.
  • the state judgment algorithm judges the sealing state based on the signal measured by the acoustic emission sensor.
  • the specific method is as follows:
  • a short period Acoustic emission signals of less than the period of the rotation axis result in contact severity and contact pressure distribution (when the contact is more derived from the compression of the two rings, the contact pressure distribution will be more dispersed; if the contact is more derived from the two rings Deflection, the distribution of contact pressure is more concentrated).
  • the function of the power of each frequency band of the acoustic emission signal to the axial center distance of the two rings and the angle between the two rings can be calibrated;
  • the feasibility analysis algorithm presets several cone height nodes of the adjustment device within the reachable range of the adjustment device, analyzes the state where the seal will be at each node, and obtains the curve of the reachable state through their interpolation. This analysis can be achieved using a more mature numerical model of mechanical seals.
  • the evaluation algorithm first obtains the expected wear rate (related to the contact pressure distribution and speed) and the leak rate (calculated from the dynamic ring deflection, static ring deflection torque, and axial compression degree) from a given seal state, and then They are converted into the economic loss rate caused by wear of the seal ring and material leakage.
  • the optimization algorithm performs one-dimensional optimization in the feasible region obtained by the foregoing feasibility algorithm to obtain a target state that can make the economic loss rate as small as possible (the process of calculating the economic loss rate from the candidate target state generated in the algorithm).
  • a target state that can make the economic loss rate as small as possible (the process of calculating the economic loss rate from the candidate target state generated in the algorithm).
  • the adjusting device Completed by the aforementioned evaluation algorithm), and analyze the cone height required to achieve the target state, and the adjusting device accordingly changes the voltage across the piezoelectric stack ring 6.
  • the simulated annealing algorithm is used for optimization:
  • Figure 4 Please refer to Figure 4.
  • the seal adopts a static ring floating design.
  • Figure 5 is a schematic diagram of the end face of the static ring.
  • the three orifices 8 on the end face of the static ring 1 are respectively guided to three independently controlled fluid sources 10.
  • the pressure of each fluid source can be independently changed within a certain range. Adjusting the pressure of these fluid sources can affect the fluid pressure distribution on the end face, thereby adjusting the sealing state.
  • eddy current displacement sensors 9 are arranged to measure the movement of the seal ring. Three of them (9-1,2,3) are evenly distributed on the back of the static ring, and one (9-4) is arranged on the back of the moving ring.
  • the state judgment algorithm uses the measured seal ring movement to determine the seal's dynamic ring deflection and static ring floating support status: the sensor's back ring motion is the moving ring's deflection movement; the static ring's back In the movement, filter out the components that are consistent with those measured by the back of the moving ring (Let the motion measured on the back of the static ring be Us and the motion measured on the back of the moving ring be Ur, define a standardized norm
  • the mechanical seal numerical model is used to analyze the state of the seal under each combination, and they can be adjusted to reach Rough borders of the state.
  • the evaluation algorithm derives the expected wear rate from the given seal state, calculates the future expected leak rate change under the influence of this wear rate, and further estimates that the cooling system will reduce the working machine to safety under such future leak change conditions Time required below temperature.
  • the optimization algorithm uses a simulated annealing algorithm, which randomly generates candidate states in the feasible region obtained by the foregoing feasibility algorithm.
  • the foregoing evaluation algorithm is used to calculate its time requirement, and a certain acceptance criterion is used to determine whether to use the new candidate state. Proceed to the next iteration. Finally, find the target state that makes the time requirement as small as possible, and after it is found, analyze the pressure of the controlled fluid source required to achieve the target state and send it to the regulating device.
  • the specific method is basically similar to that of Embodiment 1:

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Mechanical Sealing (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

一种机械密封智能调节系统，包括：监测装置，实时测量与密封相关的信号；控制装置，包括状态判断模块、可行域分析模块、评估模块和寻优模块，其中，状态判断模块解读由监测装置得到的信号以估计密封的状态，可行域分析模块依据当前状态判断调节装置的调节作用可以使密封达到的状态，评估模块对密封的状态评估价值，寻优模块从密封调节的可行域中尽可能地寻找得到较高价值的调节方式，据此对调节装置发出指令；调节装置，根据控制装置给出的指令主动地对密封施加作用。

Description

一种机械密封智能调节系统与方法 技术领域
本发明属于流体密封领域和自动控制领域，特别涉及一种机械密封智能调节系统与方法。
背景技术
机械密封是旋转机械设备中的一种常见轴端密封形式。其配对的动环和静环相对旋转，形成具有一定稳定性的摩擦副，在限制泄漏的同时减轻甚至消除接触。然而，这种来自于对密封的润滑、动力学、传热与变形的精妙设计的稳定性有时仍然无法在较强的异常因素的影响下维持摩擦副的稳定，导致密封性能下降，寿命缩短，甚至发生无预兆的失效。
针对这一问题，人们提出引入在密封中引入外加的调节装置，在实时监测的基础上，采用反馈控制的方法尝试将密封维持在某种理想状态附近。这种方法的不足之处在于，由于机械密封机理的复杂性和结构的紧凑性，调节装置在机械密封系统中的调节能力往往是有限的，这包括两个方面：一是许多异常因素是无法(或至少很难)被一种或多种特定的调节装置的功能所刚好抵消的，更何况实践上不同种类的调节装置在占用空间上可能存在干涉；二是调节装置的调节强度是有限的，尤其是在一些高参数的机械密封中(通常来说，对可靠性有极高要求的也正是高参数的密封)，密封本身的机理带来的稳定性也相当强大，调节装置所能带来的改变可能并不占据支配地位。这两点意味着，如果按反馈控制的方法设定一个确定的目标状态，这个目标状态一般是不可达的，然而作为非线性系统的密封的状态与性能的关系是复杂的，即：并非状态越接近某个高性能的目标状态，性能就越佳。进一步说，在不同的具体应用场合下，用户对密封的各方面性能(如泄漏、磨损量、扭矩等)可能有着不同的需要，应当从安全性、经济性等多个角度去综合评判对性能的需要。
发明内容
为了克服上述现有技术的缺点，本发明的目的在于提供一种机械密封智能调节系统与方法，其在实时监测并分析密封状态的基础上，依据用户要求的综合性能目标，寻找最佳的且通过调节可达的状态，并通过调节装置将密封调节到这一状态。
为了实现上述目的，本发明采用的技术方案是：
一种机械密封智能调节系统，包括：
监测装置，实时测量与密封相关的信号；
控制装置，包括状态判断模块、可行域分析模块、评估模块和寻优模块，其中，所述状态判断模块解读由监测装置得到的信号以估计密封的状态，所述可行域分析模块依据当前状态判断调节装置的调节作用可以使密封达到的状态，所述评估模块对密封的状态评估价值，所述寻优模块从密封调节的可行域中尽可能地寻找得到具有最高的安全和/或经济效益的调节方式，据此对调节装置发出指令；
调节装置，根据控制装置给出的指令主动地对密封施加作用。
所述监测装置主要包括传感器、信号预处理装置、采集卡、采集软件及必要的作为载体的终端设备。
所述与密封相关的信号包括上下游压力、膜内压力、转速、密封环温度、密封环位移、密封环间电容以及摩擦副声发射，所述调节装置对密封施加的作用为力、压强变化、形状变化以及加热/冷却中的一种或者多种组合。
所述状态判断模块对监测装置测得的信号进行滤波并按照标定关系得出被测物理量的值；所述评估模块首先由给定的密封状态计算其性能，然后将性能参数按照实际应用场景的需求综合起来，从而将每个密封状态映射为一个价值量。
本发明还提供了一种机械密封智能调节方法，实时测量与密封相关的信号，执行控制算法，生成对密封施加作用的指令，进行密封调节，其中，所述控制算法依次包括状态判断环节、可行域分析环节、评估环节和寻优环节，所述状 态判断环节解读由监测装置得到的信号以估计密封的状态，所述可行域分析环节依据当前状态判断调节装置的调节作用可以使密封达到的状态，所述评估环节对密封的状态评估价值，所述寻优环节从密封调节的可行域中尽可能地寻找得到较高价值的调节方式，据此发出指令。
所述状态判断环节中，对测得的信号进行滤波并按照标定关系得出被测物理量的值，当传感器的测量并不能提供确定密封状态的全部信息时，状态判断算法给出密封状态的概率分布，并依据调节后的信号变化作进一步判断。
所述状态判断、可行域分析和评估均依据密封的特性模型设计精确或近似计算的方法，所述密封的特性模型指特定状态的密封会带来怎样的性能和产生怎样的可监测要素，及未来状态将如何转变。
与现有技术相比，本发明的有益效果是：
针对机械密封主动调节中线性反馈算法由于调节机构的能力限制和密封系统的非线性特征而不适用的问题，根据具体的应用场合制定最优化策略。
附图说明
图1是本发明系统三个装置的典型组合方式，必要时组合方式也可进行调整。在它们的作用下，密封可以尽可能地达成具体应用场景下的最大价值，达到精准调控的目的。
图2是本发明实施例1中采用静环浮动式设计的密封结构示意图。
图3是本发明实施例1中锥高调节的示意图。
图4是本发明实施例2中采用静环浮动式设计的密封结构示意图。
图5是图3中的静环端面示意图。
具体实施方式
为了使本发明的发明目的、技术方案及技术效果更加清楚明白，以下结合附图对本发明的具体实施例进行描述。应当理解，此处所描述的具体实施例仅用以解释本发明，并不用于限定本发明。
参考图1，本发明为一种机械密封智能调节系统，其在实时监测并分析密封状态的基础上，依据用户要求的综合性能目标，寻找最佳的且通过调节可达的 状态，并通过调节装置将密封调节到这一状态，其包括：
(1)监测装置
监测装置主要包括传感器、信号预处理装置(如放大器、信号转换器等)、采集卡、采集软件，及必要的作为载体的终端设备(如工控机)。监测装置实时地测量与密封相关的多种信号，可用的通常包括上下游压力、膜内压力、转速、密封环温度、密封环位移、密封环间电容、摩擦副声发射等。
(2)控制装置
以软件和运行它的终端设备为控制算法载体。区别于传统的反馈控制，本发明控制算法主要包括以下环节：状态判断、可行域分析、评估和寻优。
状态判断环节解读由监测装置得到的信号以估计密封的状态。其对测得的信号进行滤波并按照标定关系得出被测物理量的值。对部分信号种类来说，还需要依据相应的密封模型进行推算(比如，由密封环中某点测得的温度，依据密封的传热分析来推算密封端面摩擦剧烈程度)。有时传感器的测量并不能提供确定密封状态的全部信息，此时状态判断算法给出密封状态的概率分布，并依据调节后的信号变化作进一步判断。
可行域分析环节依据当前状态判断调节装置的调节作用可以使密封达到的状态。
评估环节对密封的状态评估价值。其首先由给定的密封状态计算其性能，然后将性能参数按照实际应用场景的需求综合起来。总的说来这一环节将每个密封状态映射为一个价值量。
寻优环节从密封调节的可行域中尽可能地寻找得到较高价值的调节方式，据此对调节装置发出指令。
其中，状态判断、可行域分析和评估均依据密封的特性模型——即特定状态的密封会带来怎样的性能和产生怎样的可监测要素，及未来状态将如何转变——设计精确或近似计算的方法。
(3)调节装置
调节装置根据控制算法给出的指令主动地对密封施加作用(这种作用可能 是各种形式的，如力、压强变化、形状变化、加热/冷却等，当然也包括了多种形式作用的组合)。
以下是本发明的两个具体实施例。
实施例1：
某机械密封用于密封无危险、无污染的物料，希望在避免密封环的磨损以避免更换密封环的成本的同时，尽可能减少泄漏以提高物料产率，最终实现经济效益的最大化。
请参见图2，密封采用静环浮动式设计(静环1经由弹簧4浮动支承在静环座3上，且与静环座3间由副密封5阻隔泄漏)。将压电叠堆环6镶嵌在密封静环1上，其可在施加电压时改变密封端面的锥高δ(见图3)：锥高(本例仅涉及收敛锥)增大会增强密封的流体静压效应，增大静环与动环的间隙，从而减轻或消除接触，但会增大泄漏量。
采用静环背部对称布置的两个微型声发射传感器7测量来自密封摩擦副的声发射信号。
状态判断算法依据声发射传感器测得的信号判断密封状态。具体方式如下：
(1)根据预先测定的材料声发射谱线库(特定材料配副接触摩擦引发的声发射信号出现的若干频带，以及摩擦剧烈程度不同导致的各频带比例变化)，由一小段(时间长度远小于转轴周期的)声发射信号得出接触剧烈程度和接触压力分布(当接触更多地源于两环的压紧时，接触压力的分布会更为分散；若接触更多地源于两环的偏斜，则接触压力的分布更集中)。通过实验测定，可以标定由声发射信号各频带的功率到两环轴向中心距离和两环夹角的函数；
(2)对比两个声发射传感器测得的信号的相位来得到声源中主要成分的大致位置。由这一位置随转轴旋转的变化，及(1)得出的两环轴向中心距离及两环夹角随转轴旋转的变化，得出动环偏摆、静环偏斜力矩和轴向压紧程度。
可行性分析算法在调节装置可达的范围内预设若干个调节装置锥高节点， 分析各节点处密封将会处于的状态，并通过它们插值得到可达状态的曲线。采用已经比较成熟的机械密封数值模型即可实现这样的分析。
评估算法首先由给定的密封状态得到预期的磨损率(与接触压力的分布和转速有关)和泄漏率(由动环偏摆、静环偏斜力矩和轴向压紧程度计算出)，然后将它们折算成密封环磨损和物料泄漏带来的经济损失率。
寻优算法在由前述的可行性算法得出的可行域中进行一维寻优，以得到可以使经济损失率尽可能小的目标状态(由算法中生成的候选目标状态计算经济损失率的过程通过前述评估算法完成)，并分析达成目标状态所需的锥高，调节装置据此改变压电叠堆环6两端的电压。考虑到问题的非线性，为避免收敛到局部最优解，采用模拟退火算法进行寻优：
(1)针对可行域为一维这一特征，将可行域变换为一个状态参量p；
(2)取可行的初始状态参量p(0)，由前述评估算法计算其相应的损失率q(0)；
(3)令n＝0；
(4)基于当前状态参量，即p(n)，随机变换出p’(n+1)＝p(n)+e(q(n))，其中e是一个随机量，其服从以k1·q(n)为标准差、0为均值的高斯分布(但从分布中截去使p’(n+1)不可行的部分)；
(5)由前述评估算法计算p’(n+1)所对应的损失率q’(n+1)；
(6)若q’(n+1)≤q(n)则接受新解，即令p(n+1)＝p(n)，相应地q(n+1)＝q’(n+1)；否则，以P＝exp(-(q’(n+1)-q(n))/(k2·q(n)))的概率接受新解。若未接受新解，则令p(n+1)＝p(n)，相应地q(n+1)＝q(n)；
(7)判断是否满足结束条件(n达到上限或连续多次未接受新解)，若结束则将此p(n+1)作为结果；否则，n累加1，跳转到(4)。
实施例2：
某用于冷却系统的密封，需要在发生故障时做出应急调节，尽可能保证工作机温度降到足够低之前冷却系统保持正常工作。
请参见图4，密封采用静环浮动式设计，图5为其静环端面示意图，静环1端面上的三个节流孔8分别被导到独立受控的三个流体源10上，每个流体源的 压强都可在一定范围内独立地改变。调节这些流体源的压力可以影响端面上的流体压力分布，从而实现对密封状态的调整。其可以有效地对两环整体的靠近或远离以及静环的倾斜进行补偿，但对于其他问题(如动环倾斜、密封端面的磨损、密封支承零部件老化、流体介质含磨粒等)则无法直接补偿，但依然可能通过合理的调节来间接地减少其不利影响。
布置四个电涡流位移传感器9以测量密封环的运动。其中三个(9-1,2,3)周向均布在静环的背面，一个(9-4)布置在动环的背面。
状态判断算法由已测得的密封环运动，判断密封的动环偏摆状况和静环浮动支承状况：动环背面传感器测得的即为动环的偏摆运动；静环背面所测得的运动中，滤除与动环背面传感器测得的一致的成分(设静环背面测得运动为Us，动环背面测得运动为Ur，定义一种经标准化的范数||·||并寻找min(||Us-α·Ur||)，给出范数最小化后的Us-α·Ur)，即为静环浮动支承的状况(其进一步分解为分为轴向和两个角向共三个分量)，最终用四个参量表示密封状态。
可行性分析算法预设了三个流体源压强极限设定值的2^3＝8种组合，采用机械密封数值模型分析每种组合下密封将会处于的状态，并由它们围成调节可达状态的大致边界。
评估算法由给定的密封状态得出预期的磨损率，在考虑此磨损率影响的情况下计算未来的预期泄漏率变化，并进一步推算这样的未来泄漏变化条件下冷却系统将工作机降到安全温度以下所需的时间。
寻优算法采用模拟退火算法，在由前述的可行性算法得出的可行域中随机地变换产生候选状态，用前述评估算法计算其时间需求，并以一定的接受准则决定是否用新的候选状态进行下一步迭代。最终找到使时间需求尽可能小的目标状态，并在找到后分析达成目标状态所需的受控流体源压强，发送给调节装置。具体做法与实施例1的基本类似：
(1)将前述的表示密封状态的四个参量标准化，定义为状态向量p；
(2)取可行的初始状态向量p(0)，由前述评估算法计算其相应的时间需求q(0)；
(3)令n＝0；
(4)基于当前状态参量，即p(n)，随机变换出p’(n+1)＝p(n)+e(q(n))，其中e是一个随机向量，其服从以k1·q(n)为标准差、0为均值的四维高斯分布(但从分布中截去使p’(n+1)不可行的部分)；
(5)由前述评估算法计算p’(n+1)所对应的时间需求q’(n+1)；
(6)若q’(n+1)≤q(n)则接受新解，即令p(n+1)＝p(n)，相应地q(n+1)＝q’(n+1)；否则，以P＝exp(-(q’(n+1)-q(n))/(k2·q(n)))的概率接受新解。若未接受新解，则令p(n+1)＝p(n)，相应地q(n+1)＝q(n)；
(7)判断是否满足结束条件(n达到上限或连续多次未接受新解)，若结束则将此p(n+1)作为结果；否则，n累加1，跳转到(4)。

Claims (9)

  1. 一种机械密封智能调节系统，其特征在于，包括：
    监测装置，实时测量与密封相关的信号；
    控制装置，包括状态判断模块、可行域分析模块、评估模块和寻优模块，其中，所述状态判断模块解读由监测装置得到的信号以估计密封的状态，所述可行域分析模块依据当前状态判断调节装置的调节作用可以使密封达到的状态，所述评估模块对密封的状态评估价值，所述寻优模块从密封调节的可行域中尽可能地寻找得到具有最高的安全和/或经济效益的调节方式，据此对调节装置发出指令；
    调节装置，根据控制装置给出的指令主动地对密封施加作用。
  2. 根据权利要求1所述机械密封智能调节系统，其特征在于，所述监测装置主要包括传感器、信号预处理装置、采集卡、采集软件及必要的作为载体的终端设备。
  3. 根据权利要求1所述机械密封智能调节系统，其特征在于，所述与密封相关的信号包括上下游压力、膜内压力、转速、密封环温度、密封环位移、密封环间电容以及摩擦副声发射，所述调节装置对密封施加的作用为力、压强变化、形状变化以及加热/冷却中的一种或者多种组合。
  4. 根据权利要求1所述机械密封智能调节系统，其特征在于，所述状态判断模块对监测装置测得的信号进行滤波并按照标定关系得出被测物理量的值；所述评估模块首先由给定的密封状态计算其性能，然后将性能参数按照实际应用场景的需求综合起来，从而将每个密封状态映射为一个价值量。
  5. 一种机械密封智能调节方法，其特征在于，实时测量与密封相关的信号，执行控制算法，生成对密封施加作用的指令，进行密封调节，其中，所述控制算法依次包括状态判断环节、可行域分析环节、评估环节和寻优环节，所述状态判断环节解读由监测装置得到的信号以估计密封的状态，所述可行域分析环 节依据当前状态判断调节装置的调节作用可以使密封达到的状态，所述评估环节对密封的状态评估价值，所述寻优环节从密封调节的可行域中尽可能地寻找得到较高价值的调节方式，据此发出指令。
  6. 根据权利要求4所述机械密封智能调节方法，其特征在于，所述与密封相关的信号包括上下游压力、膜内压力、转速、密封环温度、密封环位移、密封环间电容以及摩擦副声发射，所述对密封施加的作用为力、压强变化、形状变化以及加热/冷却中的一种或者多种组合。
  7. 根据权利要求4所述机械密封智能调节方法，其特征在于，所述状态判断环节中，对测得的信号进行滤波并按照标定关系得出被测物理量的值，当传感器的测量并不能提供确定密封状态的全部信息时，状态判断算法给出密封状态的概率分布，并依据调节后的信号变化作进一步判断。
  8. 根据权利要求4所述机械密封智能调节方法，其特征在于，所述评估环节中，首先由给定的密封状态计算其性能，然后将性能参数按照实际应用场景的需求综合起来，从而将每个密封状态映射为一个价值量。
  9. 根据权利要求4所述机械密封智能调节方法，其特征在于，所述状态判断、可行域分析和评估均依据密封的特性模型设计精确或近似计算的方法，所述密封的特性模型指特定状态的密封会带来怎样的性能和产生怎样的可监测要素，及未来状态将如何转变。
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