CN103016948B - The online leakage detection apparatus of Thermal Power Station's steam-water pipe drain valve - Google Patents

Abstract

The online leakage detection apparatus of a kind of Thermal Power Station's steam-water pipe drain valve, be made up of digital temperature sensor, digital temperature signal collector, 485 telecommunication cables, light cat, optical cable and data handling machine, described digital temperature sensor adopts DS18B20, and several digital temperature sensors that same drain valve downstream drain water piping external circumferential is arranged share a digital temperature signal collection device; Described digital temperature signal collector adopts microprocessor ARM7, the signal that collection comes is passed to data handling machine by data communication circuit and processes; According to data and the variance ratio thereof of drain valve downstream wall surface temperature, the principle of Fuzzy Pattern Recognition is adopted to carry out fuzzy diagnosis to trap leaking grade.The present invention is simple by system, convenient for installation and maintenance, can on-line real time monitoring, and makes judgement promptly and accurately to trap leaking.

Description

On-line leak detection device for steam and water pipeline traps in thermal power plants

technical field

The invention relates to an online real-time leak detection device for a steam-water pipeline trap in a thermal power plant, belonging to the detection technical field.

Background technique

Steam will inevitably lose heat during pipeline transmission. When its temperature drops to the saturation temperature, it will start to condense and form condensed water, that is, drain. Water impact on steam pipelines, causing damage to pipelines and equipment. At the same time, the water in the drain pipe is recycled through the drain system, which also avoids the loss of part of the working fluid and heat.

A certain number of drain pipes are usually arranged on the steam pipes of thermal power plants, and at least one drain valve is installed on each drain pipe. The discharge of drain can be controlled by opening and closing the drain valve. During the start-up phase of the unit, the drain valves should be opened. At this time, a large amount of condensed water will be generated during the steam pipe heating process, which needs to be discharged from the steam pipe in time through the drain pipe. Once the process of starting the warm pipe is over and it enters the normal working state, the drain valve should be closed to prevent the steam from the steam pipe from entering the drain pipe and causing steam loss.

The main steam pipes, reheat steam pipes, shaft seal steam pipes, and steam extraction pipes of thermal power generating units are all equipped with drain pipes. In addition, drain pipes will also be installed on high-temperature and high-pressure water pipes such as boiler water supply pipes, economizer headers, steam drum accident water discharge pipes, and boiler regular sewage discharge pipes. Some drain valves (10) are all installed on these draining water pipelines. Drain valve is the key equipment on the drain pipeline, and one side of most of the valves works under high temperature and high pressure. During the opening and closing process of the steam trap, condensed water and steam frequently impact, corrode, and wear the valve, resulting in the trap not being closed tightly and leakage failures often occur. Leakage of steam traps can be divided into external leakage and internal leakage. External leakage refers to the leakage of steam (or hot water) from the valve body or joint to the outside after the trap fails. The external leakage of the trap can be judged by sound and phenomenon, and this kind of fault is easy to find. Internal leakage means that the steam trap loses the function of preventing steam and water, so that part of the steam or steam passes directly through the inside of the steam trap, and is discharged into the drainage system through the steam trap. Internal leakage of steam traps is common and difficult to detect. When the unit is in normal operation, if the drain valve leaks, the high-temperature and high-pressure steam or water in the steam pipe will leak into the drain pipe, and the resulting steam and water flow and heat loss will reduce the economy of the unit.

In the prior art, commonly used methods for checking internal leaks of steam traps include:

(1) Shutdown inspection method, that is, after the unit is shut down, regularly disassemble the steam trap to observe whether the internal components fail, so as to determine whether the steam trap has internal leakage. This method is cumbersome to operate, wastes a lot of time and manpower, and can only make rough judgments. It is difficult to determine small leaks. If the production needs to be carried out continuously, this method cannot be implemented.

(2) Observing the mirror method, it is difficult to distinguish the main steam and the flash steam, and sufficient experience is required. This method is only suitable for low pressure conditions, and it may also fail due to fouling of the mirror.

(3) Ultrasonic leak detection method. When high-pressure steam leaks, turbulent flow will be generated near the leak point, and ultrasonic waves will be generated at the same time, but there will be no ultrasonic waves when the trap normally discharges condensed water. The ultrasonic data at the trap can be detected by special instruments and combined with the operating parameters of the unit to determine whether there is leakage. The detection system involves a variety of knowledge fields such as machine, light (laser light to locate leaks), electricity, and sound, and involves sound wave signal conversion and processing, etc., and the system is complex. And the background noise of the environment will also interfere with the accuracy of its judgment.

(4) The thermocouple detection method is used to measure the temperature of the pipe wall or working medium before and after the valve, and judge whether there is leakage in the valve by comparing the temperature changes before and after the valve. For high-temperature and high-pressure pipelines, the temperature detection elements used in this method need to withstand high-temperature environments. From the perspective of safety, the temperature measurement points must be installed before the unit starts, otherwise after the unit is running, the steam parameters in the pipe will rise. There are many restrictions on its installation and use.

When the above method is used for on-line detection of equipment, special equipment is required to convert the measured analog signal into a digital signal (ie, A/D conversion), the system is complex and the investment in equipment is relatively large. Considering the large number of traps in thermal power plants and the complex spatial distribution, the above-mentioned detection methods have problems such as complex systems, large investment in detection equipment, and high energy consumption. In order to overcome the above problems, the present invention proposes a one-line digital thermal power plant steam-water pipeline trap leak detection device with simple system, stable operation and online real-time monitoring.

Invention content:

The purpose of the present invention is to provide a device with simple system, stable operation, on-line real-time monitoring and detection of leakage of drain valves of steam-water pipelines in power plants.

Problem described in the present invention is realized with following technical scheme:

An online leak detection device for a steam-water pipeline trap in a thermal power plant, comprising a signal collector, a data processing computer, and a digital temperature sensor installed on the drain pipeline connected to the detected steam trap, the digital temperature sensor adopts DS18B20, The signal output terminal is connected to the input port of the signal collector; the signal collector adopts a micro-processing chip ARM7, and its communication port is connected with a data processing computer through an optical cable.

In the above-mentioned on-line leak detection device for steam-water pipeline traps in thermal power plants, multiple digital temperature sensors corresponding to each detected trap are installed, all of which are installed on the downstream drain pipe of the detected trap, and around the drain pipe. Arranged on the axis, all the digital temperature sensors corresponding to one or more detected steam traps are connected to the signal input port of the same signal collector through the bus.

For the above-mentioned on-line leak detection device for steam-water pipeline traps in thermal power plants, when a single insulation layer is used outside the drainage pipeline, the digital temperature sensor is installed in the single insulation layer, and the distance from its position to the axis of the drainage pipeline, that is, the installation radius r of the digital temperature sensor is according to The following formula is calculated:

$\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; )</span>}^{\frac{\mathrm{<span\; class="notranslate">\; T</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}<span\; class="notranslate">\; ,</span>$

Among them, _r1 is the radius of the outer wall of the drain pipe; _r2 is the radius of the outer wall of the insulation layer; T1 is the temperature of the outer wall _of the drain pipe _; T2 is the temperature of the outer wall of the insulation layer; T is the maximum allowable temperature measurement value of the digital temperature sensor, not greater than 120 °C ;

When double insulation layers are used outside the drain pipe, if the interface temperature of the double insulation layers is greater than the maximum allowable temperature measurement value of the digital temperature sensor, the digital temperature sensor is installed in the outer insulation layer; if the interface temperature of the double insulation layers is lower than that of the digital temperature sensor The maximum allowable temperature measurement value, the digital temperature sensor is installed in the inner insulation layer.

The above-mentioned on-line leak detection device for steam-water pipeline traps in thermal power plants collects measurement signals from digital temperature sensors, and based on these temperature values and their rate of change, can analyze and judge whether there is leakage and the degree of leakage in the trap valve;

The leakage judgment of the steam trap is carried out according to the following steps:

The digital temperature sensor is arranged on the drainage pipeline downstream of the steam trap to be tested, wherein,

$\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>$

if: And: Δt=tt _a >δ ₂ ,

Then it can be judged that the trap is leaking;

In the formula:

t - the average temperature of the drain pipe wall;

t _i ——measured value of the i-th digital temperature sensor;

n - the number of digital temperature sensors;

τ——time;

t _a - is the ambient temperature or the temperature of the outer surface of the insulation layer;

δ ₁ , δ ₂ , δ ₃ ——alarm limits set by the user, which can be set according to the working fluid parameters in the drain pipeline and the pipeline structure; generally: δ ₁ >0.01-0.5℃/s, δ ₃ >0.01 -0.5°C/s, δ ₂ is based on the temperature difference collected and calculated under the condition of no leakage, plus 3-15°C.

by Δt, The three parameters are used as the symptom parameters of the trap leakage fault, combined with the principle of fuzzy pattern recognition, to further judge the leakage degree of the trap; .

${\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.5</span>}& {\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.25</span>}& {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; \&Greater\; Equal;</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.5</span>}& {\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.25</span>}& {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.5</span>}& {\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.25</span>}& {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>$

z ₁ ——symptom parameter Corresponding fault symptom value;

z ₂ ——the fault symptom value corresponding to the symptom parameter Δt;

z ₃ ——symptom parameter Corresponding fault symptom value;

a ₁ , a ₂ , a ₃ ——the limit value of the sharp rise of the symptom parameter, determined according to the monitored working fluid parameters in the trap;

b ₁ , b ₂ , b ₃ ——the slowly increasing limit of symptom parameters, determined according to the monitored working fluid parameters in the trap;

c ₁ ,c ₂ ,c ₃ ——the limit value of the slight increase of the symptom parameter, determined according to the monitored parameters of the working fluid in the trap;

The typical fault eigenvectors for constructing the fuzzy identification of trap leakage degree are as follows:

u ₁ =(z ₁₁ ,z ₁₂ ,z ₁₃ )=(1,1,1);

u ₂ =(z ₂₁ ,z ₂₂ ,z ₂₃ )=(0.5,0.5,0.5);

u ₃ =(z ₃₁ ,z ₃₂ ,z ₃₃ )=(0.25,0.25,0.25);

u ₄ =(z ₄₁ ,z ₄₂ ,z ₄₃ )=(0,0,0)

Among them, u ₁ , u ₂ , u ₃ , and u ₄ respectively correspond to four typical states of severe leakage, moderate leakage, slight leakage and no leakage;

According to the collected temperature data, the eigenvector under the current working condition is sorted out as u _x =(z ₁ ,z ₂ ,z ₃ ), and its fuzzy membership function is established to calculate:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}<span\; class="notranslate">\; \&rsqb;</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; ,</span>$

${\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; |</span>}{{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; ,</span>$

D=max[d _i (u _x , u _i )], i=1,2,3,4,

According to the principle of maximum membership degree, we get:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$

It can identify which of the four typical states the current operating state of the trap is close to, and then make a judgment on the degree of leakage.

In the invention, the digital temperature signal sensor is directly arranged in the thermal insulation layer of the drain pipeline downstream of the drain valve, and the sensors are connected by a bus, so the system is simple, the installation and maintenance are convenient, and the investment is small. The device can be monitored online in real time, and can make timely and accurate judgments on the leakage of the steam trap.

Description of drawings

The present invention will be further described below in conjunction with accompanying drawing.

Fig. 1 is a schematic diagram of the system configuration of the present invention;

Fig. 2 is the schematic diagram of the installation of the cross-section of the drain pipe and the digital temperature sensor;

Figure 3, Figure 4-a, and Figure 4-b are schematic diagrams for estimating the arrangement position of the digital temperature sensor in the radial direction of the drain pipe;

Fig. 5 is a schematic diagram of a partial section of the pipeline at the installation position of the digital temperature sensor;

Figure 6 is a schematic diagram of the collector.

The list of labels in the figure is: 1, digital temperature sensor; 2, bus; 3, collector; 4, 485 communication cable; 5, optical modem; 6, optical cable; 7, data processing computer; or SIS) server; 9, steam (hot water) pipeline; 10, steam trap; 11, drainage pipeline; 12, drainage pipe wall; 13, insulation layer; 14, outer wall of insulation layer.

The list of symbols used in this paper is: r ₁ , the radius of the drain pipe; r ₂ , the radius of the insulation layer; r ₃ , the radius of the interface of the insulation layer in the case of double insulation layers; r, the installation radius of the digital temperature sensor; T ₁ , the wall temperature of the drain pipe; T ₂ Temperature of the outer wall of the insulation layer; T ₃ , the temperature of the interface between the two insulation layers; T, the temperature at the digital temperature sensor; Δr, the distance between the digital temperature sensor and the outer wall of the insulation layer; λ ₁ , the thermal conductivity of the inner insulation material; λ ₂ , thermal conductivity of the outer insulation material; l, the axial length of the drain pipe.

Detailed ways

The invention relates to a leak detection device for a steam trap in a thermal power plant, which is mainly composed of a digital temperature sensor, a bus, a collector, a 485 communication cable, an optical modem, an optical cable, a data processing computer and the like. The data processing computer is located in the control room and is used for collecting temperature data, data recording and processing, leakage judgment processing, alarm signal output, etc.

When the trap leaks, the high-temperature steam and water in the pipeline will increase the temperature of the drain pipe wall downstream of the valve, and the digital temperature sensor arranged on the outside of the pipe wall will measure the temperature change, which can be detected at the trap to be checked. A number of digital temperature sensors are evenly arranged in the circumferential direction of the drain pipe to calculate the average value of the temperature change and improve the measurement accuracy. The digital temperature sensor at the same steam trap is connected to the collector in parallel through a bus.

After collecting the signal, the collector transmits it to the data processing computer for processing through the optical modem and optical cable.

The digital temperature sensor adopts DS18B20, which is a one-line digital temperature sensor produced by DALLAS company. The temperature measurement range is -55°C to +125°C, and the A/D conversion accuracy can be programmed as 9-bit to 12-bit. up to 0.0625°C. DS18B20 is suitable for long-distance multi-point temperature detection system.

The main steam pipes, reheat steam pipes, shaft seal steam pipes, air extraction pipes, feedwater heater emergency drain pipes and other pipes of thermal power generating units are equipped with drain pipes and several drain valves. It can be seen that the steam parameters at different steam traps are different, even very different, and the maximum steam temperature can be above 540°C, which is much higher than the temperature measurement range of the digital temperature sensor DS18B20. In order to ensure the safe and stable operation of the steam trap leak detection device of the power plant, the digital temperature sensor must be arranged in a reasonable position so that the maximum temperature value here does not exceed 120 °C. As shown in Figure 4, according to the principle of heat transfer, the arrangement position of the digital temperature sensor in the radial direction of the pipeline can be estimated according to the following formula:

$\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}{\mathrm{<span\; class="notranslate">\; ln</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}\mathrm{<span\; class="notranslate">\; ln</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$

Organized: $r=r_1{\left(\frac{r_2}{r_1}\right)}^{\frac{T-T_1}{T_2-T_1}},$

Then the distance between the digital temperature sensor and the outer wall of the insulation layer in the radial direction of the pipeline: Δr=r ₂ -r

When double insulation layers are used outside the drain pipe, the layout position of the digital temperature sensor in the radial direction of the pipe can be estimated according to the following formula:

$\frac{\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; \&pi;\&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; ln</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; \&pi;\&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; ln</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>$

First set r=r ₃ , calculate t ₃ , when t>t ₃ , the installation position of the digital temperature sensor is, Δr=r ₂ -r; when t<t ₃ , the installation position of the digital temperature sensor is, Δr=r ₂ -r, where, r ₁ , the radius of the drain pipe; r ₂ , the radius of the insulation layer; r ₃ , the radius of the interface of the insulation layer in the case of double insulation layers; r, the installation radius of the digital temperature sensor; T ₁ , the wall of the drain pipe Temperature; T ₂ temperature of the outer wall of the insulation layer; T ₃ , the interface temperature of the two insulation layers; T, the temperature at the digital temperature sensor; λ ₁ , the thermal conductivity of the inner insulation material; λ ₂ , the thermal conductivity of the outer insulation material; l. The length of the outer insulation layer of the drain pipe in the axial direction of the drain pipe; t is the maximum allowable temperature measurement value of the digital temperature sensor, and the value is less than 120°C.

The measurement signals of these digital temperature sensors are collected, and according to these temperature values and their rate of change, it is possible to analyze and judge whether there is leakage and the degree of leakage of the steam trap valve.

The leakage judgment of the steam trap is carried out according to the following steps:

The digital temperature sensor is arranged on the drain pipe after the drain valve to be tested, wherein,

$\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>$

if: And: Δt=tt _a >δ ₂ ,

Then it can be judged that the trap is leaking;

In the formula:

t - the average temperature of the drain pipe wall;

t _i ——measured value of the i-th digital temperature sensor;

n—the number of digital temperature sensors on the section;

τ——time;

t _a - is the ambient temperature or the temperature of the outer surface of the insulation layer;

δ ₁ , δ ₂ , δ ₃ ——the alarm limit set by the user, which can be set according to the parameters of the working medium in the drain pipeline and the structure of the pipeline. Generally: δ ₁ >0.01-0.5°C/s, δ ₃ >0.01-0.5°C/s, δ ₂ is based on the temperature difference collected and calculated under the condition of no leakage, plus 3-15°C.

by Δt, The three parameters are used as the symptom parameters of the trap leakage fault, combined with the principle of fuzzy pattern recognition, to further judge the leakage degree of the trap; .

${\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.5</span>}& {\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.25</span>}& {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; \&Greater\; Equal;</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.5</span>}& {\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.25</span>}& {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 1</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.5</span>}& {\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0.25</span>}& {\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; \&le;</span>\frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \frac{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; t</span>}}{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; \&tau;</span>}}<span\; class="notranslate">\; <</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>$

z ₁ ——symptom parameter Corresponding fault symptom value;

z ₂ ——the fault symptom value corresponding to the symptom parameter Δt;

z ₃ ——symptom parameter Corresponding fault symptom value;

a ₁ , a ₂ , a ₃ ——the limit value of the sharp rise of the symptom parameter, determined according to the monitored working fluid parameters in the trap;

b ₁ , b ₂ , b ₃ ——the slowly increasing limit of symptom parameters, determined according to the monitored working fluid parameters in the trap;

c ₁ ,c ₂ ,c ₃ ——the limit value of the slight increase of the symptom parameter, determined according to the monitored parameters of the working fluid in the trap;

The typical fault eigenvectors for constructing the fuzzy identification of trap leakage degree are as follows:

u ₁ =(z ₁₁ ,z ₁₂ ,z ₁₃ )=(1,1,1);

u ₂ =(z ₂₁ ,z ₂₂ ,z ₂₃ )=(0.5,0.5,0.5);

u ₃ =(z ₃₁ ,z ₃₂ ,z ₃₃ )=(0.25,0.25,0.25);

u ₄ =(z ₄₁ ,z ₄₂ ,z ₄₃ )=(0,0,0)

Among them, u ₁ corresponds to severe leakage, u ₂ corresponds to moderate leakage, u ₃ corresponds to slight leakage, and u ₄ corresponds to four typical states of no leakage;

According to the collected temperature data, the eigenvector under the current working condition is sorted out as u _x =(z ₁ ,z ₂ ,z ₃ ), and its fuzzy membership function is established to calculate:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}<span\; class="notranslate">\; \&rsqb;</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; ,</span>$

${\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; |</span>}{{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; ,</span>$

D=max[d _i (u _x , u _i )], i=1,2,3,4,

According to the principle of maximum membership degree, we get:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$

It can identify which of the four typical states the current operating state of the trap is close to, and then make a judgment on the degree of leakage.

Determine the installation position of the collector according to the actual situation on site, and at the same time determine that a number of digital temperature sensors at the traps share a signal collector. For example: Figure 1 shows that several digital temperature sensors at two adjacent steam traps share one collector.

Taking a 300MW utility boiler as an example, the design steam pressure is 17.5MPa and the temperature is 540℃. The outlet header of the superheater is equipped with a drain pipeline with two drain valves. The size of the drain pipe is φ42×5.5. Glass wool with a thickness of 22mm is laid outside the drain pipe for heat preservation, and a digital temperature sensor is installed on the pipe wall downstream of the drain valve. sensor. After calculation, the digital temperature sensor is installed in the insulation layer at a distance of 18mm from the surface of the outer wall of the drain pipe, which can ensure that the temperature does not exceed 120°C under various working conditions. The ambient temperature is 30°C. Through simulation calculation, it is found that the internal leakage of the trap starts from the tightly closed state. If the leakage flow rate is 0.084kg/s, after 5 minutes, the relevant parameters tend to be stable. During a transition period after the fault occurs, the wall temperature measured by the digital temperature sensor, its temperature rise rate δ ₁ , temperature difference change rate δ ₃ , and the difference between the temperature difference δ ₂ and the change with time are nonlinear, where The variation rules of δ ₁ and δ ₃ are consistent, and the variation range is 0.01-1.36℃/s. The difference δ ₂ between the wall temperature and the ambient temperature measured by the digital temperature sensor also increased from 9.7°C to 66.2°C, and the temperature difference value increased by 56.5°C. Therefore, according to the temperature collected by the digital temperature sensor, by analyzing the wall surface temperature rise rate δ ₁ , the temperature difference change rate δ ₃ , and the change law of the difference between the temperature difference δ ₂ and the ambient temperature, the leakage fault of the drain valve can be identified and resolved in time. judge.

The present invention may also have other implementation modes, and any technical solution formed by equivalent replacement or equivalent transformation shall fall within the protection scope of the present invention.

Claims (2)

1. the online leakage detection apparatus of Thermal Power Station's steam-water pipe drain valve, it is characterized in that, it comprises signal picker (3), data handling machine (7) and is arranged on the digital temperature sensor (1) on drain water piping (11) that detected drain valve (10) is connected, described digital temperature sensor (1) adopts DS18B20, and its signal output part connects the input port of signal picker (3); Described signal picker (3) adopts micro-chip processor ARM7, and its PORT COM is connected with data handling machine (7) by optical cable (6);

The digital temperature sensor (1) corresponding with each detected drain valve (10) all arranges multiple, they are all arranged on the downstream drain water piping of detected drain valve (10), and along the axis arranged of drain water piping (11), all digital temperature sensors (1) corresponding to one or more detected drain valve (10) are connected by the signal input port of bus with same signal picker (3);

When drain water piping (11) adopts single thermal insulation layer (13) outward, digital temperature sensor (1) is arranged in single thermal insulation layer (13), its position is to the distance of drain water piping (11) axis, and namely digital temperature sensor installation radius r calculates according to the following formula:

$r=r_1{\left(\frac{r_2}{r_1}\right)}^{\frac{T-T_1}{T_2-T_1}},$

Wherein, r ₁for drain pipe exterior radius; r ₂for thermal insulation layer exterior radius; T ₁for drain pipe outside wall temperature; T ₂for thermal insulation layer outside wall temperature; T is the maximum permission thermometric value of digital temperature sensor;

When drain water piping (11) adopts two thermal insulation layer outward, if two thermal insulation layer separating surface temperature is greater than the maximum permission thermometric value of digital temperature sensor (1), then digital temperature sensor (1) is arranged in external thermal insulation (15); If two thermal insulation layer separating surface temperature is less than the maximum permission thermometric value of digital temperature sensor (1), then digital temperature sensor (1) is arranged in inner thermal insulating layer (14).

2. the online leakage detection apparatus of Thermal Power Station's steam-water pipe drain valve according to claim 1, it is characterized in that, gather the measurement signal of digital temperature sensor, according to these Temperature numerical and variance ratio thereof, whether can there is to hydrophobic valve leakages, leakiness situation carries out analysis judgement;

Described trap leaking judges to carry out as follows:

Described digital temperature sensor is arranged on the drain water piping after drain valve to be measured, wherein,

$t=\frac{1}{n}\underset{i=1}{\overset{n}{\&Sigma;}}{t}_i,$

If: and: Δ t=t-t _a> δ ₂,

Then trap leaking can be judged;

In formula:

T---hydrophobic tube wall average temperature value;

T _i---the measured value of i-th digital temperature sensor;

N---the number of digital temperature sensor on section;

τ---the time;

T _a---be ambient temperature or thermal insulation layer hull-skin temperature;

δ ₁, δ ₂, δ ₃---be the alarm limits of user's setting, can according to fluid properties, the setting of pipeline configuration situation in drain water piping; Wherein: δ ₁> 0.01 DEG C/s, δ ₃> 0.01 DEG C/s, δ ₂gather on the temperature difference basis of calculating in No leakage situation, increase 3-15 DEG C;

With Δ t, three parameters as the sign parameter of trap leaking fault, and in conjunction with the principle of Fuzzy Pattern Recognition, judge trap leaking degree further; Concrete steps are: first by the amplitude of variation of each sign parameter, be converted to the fuzzy expression of sign parameter, represent four intervals of sign Parameters variation, represent the large and small degree of the amplitude of variation of each sign parameter respectively with 1,0.5,0.25,0, as follows:

$z_1=\left\{\begin{array}{cc}1& \frac{dt}{d\mathrm{\&tau;}}\&GreaterEqual;a_1\\ 0.5& b_1\&le;\frac{dt}{d\mathrm{\&tau;}}<a_1\\ 0.25& c_1\&le;\frac{dt}{d\mathrm{\&tau;}}<b_1\\ 0& \frac{dt}{d\mathrm{\&tau;}}<c_1\end{array}\right.,z_2=\{\begin{array}{cc}1& \mathrm{\&Delta;}t\&GreaterEqual;a_2\\ 0.5& b_2\&le;\mathrm{\&Delta;}t<a_2\\ 0.25& c_2\&le;\mathrm{\&Delta;}t<b_2\\ 0& \mathrm{\&Delta;}t<c_2\end{array},z_3=\left\{\begin{array}{cc}1& \frac{d\mathrm{\&Delta;}t}{d\mathrm{\&tau;}}\&GreaterEqual;a_3\\ 0.5& b_3\&le;\frac{d\mathrm{\&Delta;}t}{d\mathrm{\&tau;}}<a_3\\ 0.25& c_3\&le;\frac{d\mathrm{\&Delta;}t}{d\mathrm{\&tau;}}<b_3\\ 0& \frac{d\mathrm{\&Delta;}t}{d\mathrm{\&tau;}}<c_3\end{array}\right.,$

Z ₁---sign parameter corresponding failure symptom value;

Z ₂---the failure symptom value that sign parameter Δ t is corresponding;

Z ₃---sign parameter corresponding failure symptom value;

A ₁, a ₂, a ₃---the limit value that sign parameter sharply raises, determine according to fluid properties in monitored drain valve;

B ₁, b ₂, b ₃---the limit value that sign parameter slowly raises, determine according to fluid properties in monitored drain valve;

C ₁, c ₂, c ₃---the limit value that sign parameter slightly raises, determine according to fluid properties in monitored drain valve;

The typical fault characteristic vector building the fuzzy diagnosis of trap leaking degree is as follows:

u ₁＝(z ₁₁,z ₁₂,z ₁₃)＝(1,1,1)；

u ₂＝(z ₂₁,z ₂₂,z ₂₃)＝(0.5,0.5,0.5)；

u ₃＝(z ₃₁,z ₃₂,z ₃₃)＝(0.25,0.25,0.25)；

u ₄＝(z ₄₁,z ₄₂,z ₄₃)＝(0,0,0)

Wherein, u ₁, u ₂, u ₃, u ₄corresponding serious leak, moderate leakage, minor leakage and No leakage four kinds of typicalnesses respectively;

According to the temperature data gathered, the characteristic vector that arrangement obtains under current working is u _x=(z ₁, z ₂, z ₃), set up its fuzzy membership functions, calculate:

$S_{u_i}\left(u_x\right)={\&lsqb;1-\frac{d_i(u_x,u_i)}{D}\&rsqb;}^2,i=1,2,3,4$

$d_i(u_x,u_i)=\frac{\left|z_1-z_{i1}\right|+\left|z_2-z_{i2}\right|+\left|z_3-z_{i3}\right|}{z_{i1}+z_{i2}+z_{i3}},i=1,2,3,4,$

D＝max[d _i(u _x,u _i)]，i＝1,2,3,4，

According to maximum membership grade principle, obtain:

$S_{u_i}\left(u_x\right)=\max \left(S_{u_1}\right(u_x),S_{u_2}(u_x),S_{u_3}(u_x),S_{u_4}(u_x\left)\right),$

Namely which state in the running state that identifiable design drain valve is current and four kinds of typicalnesses is close, and then makes the judgement of leakiness.