PHM Prognostics and Health Management System

发布时间：2026-10-16

作者：

PHM Prognostics and Health Management System

Built on a five-in-one smart sensor, the system fuses vibration, temperature, noise, ultrasound and electromagnetic field measurements to deliver full-lifecycle condition monitoring, early anomaly detection and predictive maintenance for critical equipment.

Beijing ZhongYuanTong Science & Technology Co., Ltd.　|　From reactive repair to active health management

01 Industry Context

Unexpected failures on critical equipment

Critical equipment on the plant floor is highly prone to unexpected breakdowns during long-term operation. Once a fault occurs, production scheduling is disrupted, the production plan is halted, and unplanned downtime brings direct economic loss and lost capacity.

Equipment breakdownScheduling disruptionUnplanned downtimeLost capacity

Where traditional maintenance falls short

Conventional practice largely relies on emergency repair — fix it after it breaks. It is costly, it carries risk, and it severely disrupts production continuity. Fixed-interval maintenance, on the other hand, tends to lead to over-maintenance, wasting spare parts and labour.

Reactive repairHigh costHigh riskProduction continuity

02 What PHM Is

From reacting to failures to managing equipment health

PHM stands for Prognostics and Health Management. It is a health management framework covering the entire equipment lifecycle, built on industrial IoT, sensing technology, data analytics and artificial intelligence.

The key difference from conventional maintenance lies in real-time condition monitoring that enables early anomaly detection, early failure warning and early service scheduling — commonly referred to as predictive maintenance and condition-based maintenance.

Detect earlyWarn earlyService early

The five-in-one smart sensor is mounted on the equipment; five measurement dimensions feed the edge diagnostic or cloud platform, which issues warnings before a failure develops (schematic)

03 Core Capabilities

(1) Early anomaly detection across five dimensions

Fusing vibration, temperature, noise, ultrasound and electromagnetic field measurements reveals early-stage anomalies that manual inspection and routine monitoring tend to miss, creating a response window for maintenance teams.

(2) Remaining useful life prediction

Combining design parameters, operating load and environmental conditions, the system calculates the remaining life of core components and provides a data basis for scheduling maintenance — turning “when to repair” into an informed decision.

(3) Maintenance decision support

Taking production schedules, spare part inventory and fault severity into account, the system helps generate a sounder maintenance plan, avoiding unnecessary shutdowns and improving equipment utilisation.

(4) An integrated data chain

The sensor supports multiple communication methods and uploads data to an edge diagnostic system or cloud platform. Built-in algorithm models then perform condition analysis and health assessment, closing the loop from data collection and feature analysis to decision support.

04 Applicable Equipment

Rotating and electromechanical critical equipment

Applicable to motors, robots, transformers, inverters, reducers, pumps, fans, compressors, hoisting equipment and conveyor systems.

MotorsRobotsTransformersInvertersReducersPumpsFansCompressorsHoistsConveyors

05 Value to Operations

Healthier equipment, smoother production

By detecting hidden risks before equipment actually fails, the system reduces unplanned downtime, keeps production on schedule and lowers overall maintenance cost — keeping equipment healthier, production smoother and companies more competitive.

When equipment runs, profits keep flowing.

06 Industry Direction

Predictive maintenance in the digital transformation

As digital transformation, smart manufacturing and industrial internet development continue to advance, predictive maintenance in high-end manufacturing, smart mines and smart factories is entering a sustained growth phase, with strong digitalisation demand and substantial room for cost reduction.

As a key component of industrial intelligent transformation, PHM is gradually extending from large high-end equipment to small and medium manufacturers, becoming a supporting tool for digital upgrades across more industries.

Note: the capabilities described above are stated at system capability level. Actual performance depends on site conditions, sensor installation and production rhythm, and is subject to the formal technical proposal and contract agreement.

Beijing ZhongYuanTong Science & Technology Co., Ltd.
PHM Prognostics and Health Management System

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